tag:blogger.com,1999:blog-68947390877906082612024-03-06T06:33:57.406+00:00under the raedarAlasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comBlogger238125tag:blogger.com,1999:blog-6894739087790608261.post-28972581916430055912015-12-01T22:53:00.003+00:002016-09-02T10:55:41.423+01:00Blog retrospective<div style="text-align: justify;">
This blog is now officially archived because I'm moving on to other things (including a <a href="http://www.statsmapsnpix.com/" target="_blank">new blog</a>, which I launched at the end of 2015). However, I thought it would be good to do one final post here to wrap things up - and to encourage anyone thinking about blogging to give it a go. I've not exactly set the world alight with the stuff on here, but quite a few people have found it useful and it's led to some very interesting work. Someone once even said they were a 'big fan'. Anyway, back in 2007 when I was a Research Associate at the University of Manchester, my colleague and car-sharing partner <a href="https://twitter.com/actualal" target="_blank">Alex Hardman</a> encouraged me to start blogging. So I did, and here I am eight years later. It wouldn't be undertheraedar without a map, so here's one showing page views by country (click all images to enlarge).</div>
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRGQJlp3PEpD6gf9bBaivcJoIjfP146TfAGE9aRg6VlKUnZBQRpcn2W1w8kkn2lOnAaMECgqQ7SaSkff7L1jOZO7ca5Jszf97cxEsQyByXQt2RkbZrZ1nnCIHYY0Xu0iP_UmqCOXZCGnw/s1600/pageviews.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRGQJlp3PEpD6gf9bBaivcJoIjfP146TfAGE9aRg6VlKUnZBQRpcn2W1w8kkn2lOnAaMECgqQ7SaSkff7L1jOZO7ca5Jszf97cxEsQyByXQt2RkbZrZ1nnCIHYY0Xu0iP_UmqCOXZCGnw/s320/pageviews.png" width="247" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The United States was going to overtake the UK, so I had to stop.</td></tr>
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The blog has led to collaboration with people like Simon Rogers at Google - previously with The Guardian and Twitter, and led to lots of media contacts, <a href="https://www.google.co.uk/search?q=%22alasdair+rae%22&oq=%22alasdair+rae%22&aqs=chrome..69i57.2668j0j1&sourceid=chrome&es_sm=122&ie=UTF-8#q=%22alasdair+rae%22&tbm=nws" target="_blank">news stories</a> and idea-sharing with other academics. It's also enabled me to get some of the findings from my academic papers out to a wider audience - which is partly why I began writing it in the first place. But which posts have been the most popular? Well, that's an interesting story and here's a little chart showing the top ten - including a major outlier at number one.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0t7UACJZEVBcAvNRshcX_cqIMjNuThHkb-_XAVHAezB6svJZq_ZmNAx6j1GzZC99uzWl_MF9OT4Nth7lw7eIjCEXwiYHcaqqFUZmsoLS0SLP59tIQhu10PDQvmun1KkxnTu8n2D3v48s/s1600/posts.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="209" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0t7UACJZEVBcAvNRshcX_cqIMjNuThHkb-_XAVHAezB6svJZq_ZmNAx6j1GzZC99uzWl_MF9OT4Nth7lw7eIjCEXwiYHcaqqFUZmsoLS0SLP59tIQhu10PDQvmun1KkxnTu8n2D3v48s/s320/posts.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Note to self - write stuff about London on new blog</td></tr>
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Twitter obviously helped a lot. Alex Hardman also encouraged me to get on Twitter early, so I signed up almost straight away but just couldn't get it so abandoned it and came back to it relatively late, in July 2011. You can kind of see how my blog traffic developed since then in this line graph, which peaked at over 13,000 page views in October 2015.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixvIytgYkR4Tj1ET4s9TTMIzWDT6PxC2j4mbpW1YXM5q4oXw-AhpUeRGkUzVU_h2glgGWmOohMEaqoF33s03MnK-juDiR2bRTDE1uqItx6D0_0DoPBYX6IjFg2HRt-K9Ssv2d4-U5D4EI/s1600/growth.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="150" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEixvIytgYkR4Tj1ET4s9TTMIzWDT6PxC2j4mbpW1YXM5q4oXw-AhpUeRGkUzVU_h2glgGWmOohMEaqoF33s03MnK-juDiR2bRTDE1uqItx6D0_0DoPBYX6IjFg2HRt-K9Ssv2d4-U5D4EI/s320/growth.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Peaks and troughs, but reasonable level of growth over time</td></tr>
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Where did my traffic come from? A typically eclectic range of sources but a lot from Google. You can see this in the Referring URLs and Referring Sites charts below. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBlNNgAysNGMavcq_nwttChiZWM3gmtH0bc6zqOWUfCrme5JJAG2YTDGWjWH8e20fVaVGCmAxdAdB2k_Om7sUEr9WowrdpVe9_fg2cAuRnMOYxma4-2LN3HSDnpMJaozyhU0g6ZNV7KRQ/s1600/referring.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="244" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBlNNgAysNGMavcq_nwttChiZWM3gmtH0bc6zqOWUfCrme5JJAG2YTDGWjWH8e20fVaVGCmAxdAdB2k_Om7sUEr9WowrdpVe9_fg2cAuRnMOYxma4-2LN3HSDnpMJaozyhU0g6ZNV7KRQ/s320/referring.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Am I big in Wisconsin?</td></tr>
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What about the tech battles? The battle of the browsers? You can see from the data below that Chrome wins the browser war, Windows wins the operating system war and that 596 page views came from Unix. </div>
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<table cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9xESmsPqT0WyrcMoRgexHqiWH3NJK4POYcnvJxiY8zUtU1QWcHKIOFKmKIzwqz84P5ZDGb8cvwQepZktS7RYtMf9f1lsjCj-8G1nKn_qGQVvGip4FHIG6oyfa8XbBqafXWfWPK8r9U8E/s1600/techbattle.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh9xESmsPqT0WyrcMoRgexHqiWH3NJK4POYcnvJxiY8zUtU1QWcHKIOFKmKIzwqz84P5ZDGb8cvwQepZktS7RYtMf9f1lsjCj-8G1nKn_qGQVvGip4FHIG6oyfa8XbBqafXWfWPK8r9U8E/s320/techbattle.png" width="229" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">William Playfair invented the pie chart in 1801</td></tr>
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Total page views all time? 403,984 (as of 2 Sept 2016), but of course there are all sorts of views on the accuracy of blogger stats vs Google Analytics, which normally come out with lower figures (often around half). But even if it was just 300,000 bots viewing my pages, I know for sure some actual humans looked at my posts because they told me, so that makes it worthwhile. </div>
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In a world where an academic paper with 50 citations is quite a big deal, getting a few hundred thousand page views is a nice way to make you feel like you can reach a wider audience. Some people may not like some of the stuff I posted and some of it is - looking back - slightly embarrassing but then that's all part of the learning experience. </div>
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If you've followed this site, or just looked once, thanks for taking an interest. I'll be back with new stuff - and more maps and stats - in the new year (or possibly before). If you're thinking about blogging, give it a bash. It can be hard to keep publishing content but I've found it really worthwhile.</div>
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Alasdair Rae</div>
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Sheffield</div>
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1 December 2015</div>
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(updated 2 September 2016)</div>
Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-50435757616043420622015-11-09T21:39:00.000+00:002015-11-09T21:39:53.540+00:00Premier league poverty, 2015<div style="text-align: justify;">
Over the past decade I've spent a lot of time looking at <a href="http://ajrae.staff.shef.ac.uk/imd15/" target="_blank">patterns of deprivation</a> across the UK. One thing I've often noticed is the way football grounds regularly appear in the very poorest neighbourhoods. I've blogged on this topic a few times in the past, most notably <a href="http://www.undertheraedar.com/2012/11/premier-league-poverty.html" target="_blank">in 2012</a> when I looked at the location of English Premier League grounds in relation to the deprivation level of their areas. I also <a href="http://www.undertheraedar.com/2009/11/british-national-grid-and-google-maps.html" target="_blank">noticed this</a> in relation to the Scottish Index of Multiple Deprivation when looking at the East End of Glasgow in 2009. Given the history of football, its <a href="http://www.amazon.co.uk/Father-Other-Working-Football-Heroes/dp/0224072676" target="_blank">industrial working class origins</a>, the development of British cities, and land values (to name just a few factors), none of this should be a surprise. But since a new English deprivation dataset was released in September, I wanted to revisit the topic and make a few maps, just to see if anything has changed. That's what I've done here - one map showing the location of each Premier League ground and the deprivation level of the area it sits in - and its wider neighbourhood. Further explanation follows below.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHo7BoRHtzxQVkfYwtotSNK5OEag3A5T21AVVSOYI-yH3JaV5Lrtk-MdbcS5fq3IR9uNhce2DLYIV3tHlwef7B_SpEd6t_Ti_E0vquIv3AzF8p9fc8ctUA59xRCK5pEaQ5Q0ZLR3-ZBpE/s1600/output_1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiHo7BoRHtzxQVkfYwtotSNK5OEag3A5T21AVVSOYI-yH3JaV5Lrtk-MdbcS5fq3IR9uNhce2DLYIV3tHlwef7B_SpEd6t_Ti_E0vquIv3AzF8p9fc8ctUA59xRCK5pEaQ5Q0ZLR3-ZBpE/s320/output_1.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Note the blue area to the north east - now Highbury Square</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicvaz9f1aT_CWI8xuhcr86Qd7QzVO-c5JAJU-XKONzLqKIS4YDyx1ySNKlQJvmxcgc30U1zcaVczqTSC5PDk0p5k_GUkLzkZBRXsUtKBpSmYj7fem7hyphenhyphenDnM6YHF48cbtEyb_qsnU1nVRg/s1600/output_2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEicvaz9f1aT_CWI8xuhcr86Qd7QzVO-c5JAJU-XKONzLqKIS4YDyx1ySNKlQJvmxcgc30U1zcaVczqTSC5PDk0p5k_GUkLzkZBRXsUtKBpSmYj7fem7hyphenhyphenDnM6YHF48cbtEyb_qsnU1nVRg/s320/output_2.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Most areas in the neighbourhood are in the 20% most deprived</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjuIdpaAogYeTmRWHP6lNtWdixspu9ITXWWfQAXsQi5QUsHW6l3_iIHZvi22EPd1IRZGtWQgDFTGx4sb_49CKaKSppwTdY0-ZhsvSphBxtd-3cTdYsaYMofs8r2wQAAqwhUIejKwIOkbRQ/s1600/output_3.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjuIdpaAogYeTmRWHP6lNtWdixspu9ITXWWfQAXsQi5QUsHW6l3_iIHZvi22EPd1IRZGtWQgDFTGx4sb_49CKaKSppwTdY0-ZhsvSphBxtd-3cTdYsaYMofs8r2wQAAqwhUIejKwIOkbRQ/s320/output_3.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Bournemouth is the one big exception - it's at the opposite end of the scale</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEifnvqbxIXij_o3UL26qxzGZiC336XAUJZ8vRGSXxyjcWI8Q7oyBuT2I6EIbfDbRftNG9jdopvELyTFmxva3nDNWQ6V7QvZP61puogpeXaz5o2LFRa4n18ae5LZ3Ls-dYolthNqtVIsLGM/s1600/output_4.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEifnvqbxIXij_o3UL26qxzGZiC336XAUJZ8vRGSXxyjcWI8Q7oyBuT2I6EIbfDbRftNG9jdopvELyTFmxva3nDNWQ6V7QvZP61puogpeXaz5o2LFRa4n18ae5LZ3Ls-dYolthNqtVIsLGM/s320/output_4.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Stamford Bridge is in a much more mixed area than most</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjpAda3Q2H4SdLr530yca9vYlRBGoq8EN3TrAebf7hQf-zyLRF2WGVxHdyt9g0emjTsDImN-GBXf_6Hw_co1CP1h7Kz_RPrJJVfAOtOdOW6zLire9VdOS3KfGEnjpYPQY5F_A6EIm6XkRU/s1600/output_5.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjpAda3Q2H4SdLr530yca9vYlRBGoq8EN3TrAebf7hQf-zyLRF2WGVxHdyt9g0emjTsDImN-GBXf_6Hw_co1CP1h7Kz_RPrJJVfAOtOdOW6zLire9VdOS3KfGEnjpYPQY5F_A6EIm6XkRU/s320/output_5.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Selhurst Park sits right beside some more deprived areas</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfyAJuohho3Jf2aA_CZq2cwZpEPw11r-LwzPQq9uq23mmXBnwIcWZ7CchJGRUsGmDCUCM39rV0Jlhf0T4Aj7cb1lHuR7xkZPaOTfoTtHjfU1xPm8CmO2B4D4HTyuuekgqxKpBYnV19Se8/s1600/output_6.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhfyAJuohho3Jf2aA_CZq2cwZpEPw11r-LwzPQq9uq23mmXBnwIcWZ7CchJGRUsGmDCUCM39rV0Jlhf0T4Aj7cb1lHuR7xkZPaOTfoTtHjfU1xPm8CmO2B4D4HTyuuekgqxKpBYnV19Se8/s320/output_6.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Goodison and Anfield look very similar - only about half a mile apart</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi74tDO3E5MIXEmixX1SvRwTgyfzjv-sxOtMSkgRXPRIT8RBycCIKUskpNQNKhaoN4lB8xtpADNQZosiJjsBMc90iAi4snv9DIABvSvnlOV6mKynAJgWadzKplDUu4Z1kC9Z79l9yBJpmk/s1600/output_7.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi74tDO3E5MIXEmixX1SvRwTgyfzjv-sxOtMSkgRXPRIT8RBycCIKUskpNQNKhaoN4lB8xtpADNQZosiJjsBMc90iAi4snv9DIABvSvnlOV6mKynAJgWadzKplDUu4Z1kC9Z79l9yBJpmk/s320/output_7.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The wider area of Leicester's ground is more mixed</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhA8UPPH7MbRY-qmfSVN8I19WRdMLRLBOYvnuamZoSdcicZioAL6fum9O7GTk6iSnSf1J7cR3GSb36q5yfXA_kBO9x5-yXt9sbGwyUz9iS6m0Hsf-WTFZz7jfmtNm1Jkn4gsiyGJrUC_qg/s1600/output_8.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhA8UPPH7MbRY-qmfSVN8I19WRdMLRLBOYvnuamZoSdcicZioAL6fum9O7GTk6iSnSf1J7cR3GSb36q5yfXA_kBO9x5-yXt9sbGwyUz9iS6m0Hsf-WTFZz7jfmtNm1Jkn4gsiyGJrUC_qg/s320/output_8.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">This is quite typical of much of north Liverpool</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDKsA55pqcZoZgxVFTORGvy1moUoiCFwcZ4v6kKbsSCw4lHmpULkylDL42YkSAQjQzVMCp5y29ILt0vH5k43-2UOzeU80c0EbBi6DcgMO6cbTZOX1neeBDsgG5IgQ3uH3TdGvSc6BYxcc/s1600/output_9.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDKsA55pqcZoZgxVFTORGvy1moUoiCFwcZ4v6kKbsSCw4lHmpULkylDL42YkSAQjQzVMCp5y29ILt0vH5k43-2UOzeU80c0EbBi6DcgMO6cbTZOX1neeBDsgG5IgQ3uH3TdGvSc6BYxcc/s320/output_9.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Manchester City play in the most deprived area of any top flight team</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilDbybac8bzNWlMUDgxUb7Pw7r76idAWeUybvmCfzYJh0DdG7JS_hF30S5fAFIgRBHLrJpGHrpCM6W_c2gYl6zZomJN2tRbQeXPxkW5E8phfcqXsAQ9cgvVVVQoMBJn8uspMBIt9Xw6ng/s1600/output_10.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEilDbybac8bzNWlMUDgxUb7Pw7r76idAWeUybvmCfzYJh0DdG7JS_hF30S5fAFIgRBHLrJpGHrpCM6W_c2gYl6zZomJN2tRbQeXPxkW5E8phfcqXsAQ9cgvVVVQoMBJn8uspMBIt9Xw6ng/s320/output_10.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Manchester United are situated in a more mixed land use area</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhIsUT1G9qBcBACdFvdQldzdnOg0dxEgz60jiz3S4Ys9zlQtehdE0Sc0jwIZOB_JKBEVMr_lYFypFrwvSBeknPLxEvmPB67RmbH4165c4WN_d-HCX34S0zn0pjomggHrtDDy-1evHU_VPs/s1600/output_11.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhIsUT1G9qBcBACdFvdQldzdnOg0dxEgz60jiz3S4Ys9zlQtehdE0Sc0jwIZOB_JKBEVMr_lYFypFrwvSBeknPLxEvmPB67RmbH4165c4WN_d-HCX34S0zn0pjomggHrtDDy-1evHU_VPs/s320/output_11.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Newcastle United's pitch is split between areas - I've based this on majority area</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh6E5U8xsZJ0ENvydf72yd-yHbBWsZC3SXO9hBknFoMKm2Huk5png8UXa6aea0f8OLRxazWt3Dsmj-YUUBDx4CkrFcc4r3bo6lDgRdEwU2wnamctk-RLX3OL0IQO7gfUEb6ydhTO6jgVR4/s1600/output_12.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh6E5U8xsZJ0ENvydf72yd-yHbBWsZC3SXO9hBknFoMKm2Huk5png8UXa6aea0f8OLRxazWt3Dsmj-YUUBDx4CkrFcc4r3bo6lDgRdEwU2wnamctk-RLX3OL0IQO7gfUEb6ydhTO6jgVR4/s320/output_12.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Norwich City's ground is also in a more mixed neighbourhood</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlXVsUwe4I9Y67b4ZoPOE27bIrEFAaG47XIDBsyzdXdZyWr22stbHWjdgwhP3GoUwhmRQtp1BrXZVG1Nzb1xw1HclZmq5mYEITWK7L1vsYPxTAHHel2Xd_TnyNzwFNK_UFDV2zHf5Zeko/s1600/output_13.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjlXVsUwe4I9Y67b4ZoPOE27bIrEFAaG47XIDBsyzdXdZyWr22stbHWjdgwhP3GoUwhmRQtp1BrXZVG1Nzb1xw1HclZmq5mYEITWK7L1vsYPxTAHHel2Xd_TnyNzwFNK_UFDV2zHf5Zeko/s320/output_13.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">St Mary's is situated in one of the city's most deprived zones</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhOjzj-BZ_81vSidSvowC5nTO3wBvZQWzZ-MuEXIT_3DmiPC07yFNcwwPhXg7ZEVtOaowgMOvTNVVeEZTMT0gsr8bA2C3v1qDA2FD014AwpeKQgfrdVIEkaROcsHcjpkyKCQrq2-8S94tY/s1600/output_14.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhOjzj-BZ_81vSidSvowC5nTO3wBvZQWzZ-MuEXIT_3DmiPC07yFNcwwPhXg7ZEVtOaowgMOvTNVVeEZTMT0gsr8bA2C3v1qDA2FD014AwpeKQgfrdVIEkaROcsHcjpkyKCQrq2-8S94tY/s320/output_14.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Stoke also play in quite a deprived area - though there's more variation nearby</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-_iqYFM8YGNZJgjw5Q7N7J2DnDlGsvWFtHIoqpqRLcVJEh-m7lvISJHk3RGSXXrt1ahMpopfls1NzHI-y-_PaiEOFQ2bj86UyoLERlLN-phye7OdYgTU1N37lVvUsTbFkZlNeRfi7XHQ/s1600/output_15.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-_iqYFM8YGNZJgjw5Q7N7J2DnDlGsvWFtHIoqpqRLcVJEh-m7lvISJHk3RGSXXrt1ahMpopfls1NzHI-y-_PaiEOFQ2bj86UyoLERlLN-phye7OdYgTU1N37lVvUsTbFkZlNeRfi7XHQ/s320/output_15.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Like many newer stadiums, this ground is in a slightly more mixed area</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgOO_iRlJdAIH3Ke2iMfXJi3mA6mzQbQXYfENMiva8uqa9GclkcqnzO47_AV2jpfMOBeIdPHFhJf2qSzV7R8866gautn4lB3UyRb5lwSBlBy-1EDlP4sOym7D61F_lfl3-vHoGCq1i4af0/s1600/output_16.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgOO_iRlJdAIH3Ke2iMfXJi3mA6mzQbQXYfENMiva8uqa9GclkcqnzO47_AV2jpfMOBeIdPHFhJf2qSzV7R8866gautn4lB3UyRb5lwSBlBy-1EDlP4sOym7D61F_lfl3-vHoGCq1i4af0/s320/output_16.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The Welsh deprivation dataset is used here - but similar story to be told</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirvppf22F1h78lBtGe-Qy_lX6R3A5E-28_Wg3my3QuiHXdXg-JLfL-b10xanR_qJPV5AyKbggKDJihSdw1hVE8JlR6Xw3eyPK0cQsdnBAwYQUXUzXqeL8x2nZlliCX03jgev1XJ_CxDdo/s1600/output_17.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEirvppf22F1h78lBtGe-Qy_lX6R3A5E-28_Wg3my3QuiHXdXg-JLfL-b10xanR_qJPV5AyKbggKDJihSdw1hVE8JlR6Xw3eyPK0cQsdnBAwYQUXUzXqeL8x2nZlliCX03jgev1XJ_CxDdo/s320/output_17.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Post-riots, much has been said of <a href="http://www.theguardian.com/artanddesign/2015/mar/22/tottenham-regeneration-londons-most-deprived-spurs-stadium" target="_blank">regeneration</a> in this area of London</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjD54BsCnIz3Wj0FZkjsR5_IJmoQTITZxr4qn0C5T-0SzjCIfBBhi_ffjy1iZHY3Kr6pw25HlJRfp_vRBza1DdCYFqvckEKTnfqfv7NX6SdGgrTWG5Cy4MtczkT04nJdWjcwYJDirBESo4/s1600/output_18.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjD54BsCnIz3Wj0FZkjsR5_IJmoQTITZxr4qn0C5T-0SzjCIfBBhi_ffjy1iZHY3Kr6pw25HlJRfp_vRBza1DdCYFqvckEKTnfqfv7NX6SdGgrTWG5Cy4MtczkT04nJdWjcwYJDirBESo4/s320/output_18.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Watford play in a much less deprived locality</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDy5diWkTK7m2r_7OBJrrIYrhbLZaN5edbQTabtAIEwH-_Rs9Gq2zY-qW0MX0ytCOvnfOGpn8W2K0icA65mFOR58Dkbh4wIcET2UDU58hozj_fxm2fFK0Vd88SWScRhLbNAtt6B-HdNKo/s1600/output_19.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgDy5diWkTK7m2r_7OBJrrIYrhbLZaN5edbQTabtAIEwH-_Rs9Gq2zY-qW0MX0ytCOvnfOGpn8W2K0icA65mFOR58Dkbh4wIcET2UDU58hozj_fxm2fFK0Vd88SWScRhLbNAtt6B-HdNKo/s320/output_19.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">West Brom's ground is in the most deprived decile of England</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgnm_sGi2LFB-D9MtQiNAAJUuWFaWRZMoifuajwWxAqVkzzVKVZyzhfNqGpfjpSEvSN5ZbsQ-bLo0zE7C-_sha-QHf8gRwlnw2yXYPwIOulosqTDEz_6TjJuv4LTpVINwAKFrTjJEzAGDQ/s1600/output_20.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgnm_sGi2LFB-D9MtQiNAAJUuWFaWRZMoifuajwWxAqVkzzVKVZyzhfNqGpfjpSEvSN5ZbsQ-bLo0zE7C-_sha-QHf8gRwlnw2yXYPwIOulosqTDEz_6TjJuv4LTpVINwAKFrTjJEzAGDQ/s320/output_20.png" width="280" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Another ground split between areas - but still more deprived than not</td></tr>
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<b>What does all this tell us?</b></div>
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The most obvious thing to emerge from this simple mapping exercise is that more than half of all Premier League grounds are located in areas among the 20% most deprived in the country, but a good few are not. Two in particular - Bournemouth and Watford - are in much less deprived areas. Nonetheless, if you scroll through the maps quickly, the main colour you'll see is red (for the 20% most deprived). When I see <a href="http://www.independent.co.uk/voices/comment/using-sport-to-tackle-deprivation-is-a-winner-9273566.html" target="_blank">stories in the news</a> about the ability of sport to tackle deprivation, I'm generally all for it, but then sometimes I make a mental comparison between the <a href="http://www.theguardian.com/football/2015/apr/29/premier-league-finances-club-by-club" target="_blank">wage bills</a> of some teams and the neighbourhoods they're located in and I think we've barely scratched the surface of what's possible when we talk of the potential for elite sport to help transform poorer areas. Post-Olympics, this has kind of been forgotten. Having said this, it is good to see that the Premier League and FA's Football Foundation <a href="http://www.footballfoundation.org.uk/funding-schemes/premier-league-the-fa-facilities-fund/" target="_blank">provides money for grass roots development</a> in the most deprived areas as defined by this very same dataset. </div>
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<b>What does it not tell us?</b></div>
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Quite a lot, and I wouldn't want anyone to think that I've done this to pick on any one team. I'm just curious about the relationship between these football grounds and underlying patterns of deprivation because when I look at the data as I map it, I often notice the stadia. It doesn't tell us anything about cause and effect, whether teams are trying to do anything to boost the fortunes of their local areas or what the areas themselves are like to live in. If you want to know more about the underlying data, read <a href="https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/464430/English_Index_of_Multiple_Deprivation_2015_-_Guidance.pdf" target="_blank">this briefing</a> from the Government. Does having a Premier League football team in your area make you poor? Of course not. </div>
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<b>Some of the grounds look the wrong shape - why?</b></div>
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I used building footprint data from the Ordnance Survey in the maps above and the shapes of the grounds are as they were in the original dataset - with the exception of Vicarage Road, which for some reason wasn't enclosed on one side so I made my own version. I've just added a little glow around each ground to make it stand out and then added in the footprints of all other buildings in the wider neighbourhood to help people identify nearby features and roads.</div>
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<b>What about when a ground is split between areas?</b></div>
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I could have taken the average deprivation rank here and used that figure but instead I chose to use the deprivation rank of the area that the majority of the playing surface was located in. This was only really an issue for Arsenal, Newcastle and West Ham - and only really notable in Newcastle. </div>
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<b>Explain that 'deprivation percentile' thing again please</b></div>
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In England, there are 32,844 areas known as Lower Super Output Areas. These LSOAs are small areas which the government use to report all kinds of statistics, including Census data. When they publish their <a href="https://www.gov.uk/government/statistics/english-indices-of-deprivation-2015" target="_blank">Indices of Deprivation</a>, they give each one of the 32,844 areas a rank, from 1 (most deprived in England) to 32,844 (least deprived in England). Therefore, it's a relative measure that allows us to compare one area with another, all across the country. The data are often split into five or ten chunks (quintiles or deciles) for reporting purposes but here I've decided to use 'percentiles' as it's more precise. If an area is in percentile 5, it's among the 5% most deprived in England, and so on. If it's in percentile 95 (like Bournemouth's ground) then we can say it's not very deprived at all and actually highly likely to be a very affluent area. In the case of Swansea City, I've used <a href="http://gov.wales/statistics-and-research/welsh-index-multiple-deprivation/?lang=en" target="_blank">Welsh deprivation data</a> from 2014. This classifies places in almost exactly the same way, although there are 1,909 areas in Wales rather than 32,844. These areas have an average population of around 1,600.</div>
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<b>Isn't this all just pointless area classification?</b></div>
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You might think so, but the Government use these Indices to make all sorts of important decisions, in healthcare and education for example. If you're in an area classified as being among the 20% most deprived, for example, you might find that you're eligible for some kind of funding - there are loads of examples of uses, with <a href="http://archive.sportengland.org/funding/active_women/assessment_criteria/indices_of_deprivation.aspx" target="_blank">sport</a> being one of many. You can find quite a few other examples in section 1.4 (p. 8) of <a href="https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/464597/English_Indices_of_Deprivation_2015_-_Research_Report.pdf" target="_blank">this report</a>. We must also remember that not all people living in areas classified as 'deprived' or 'not deprived' match that description - this dataset classifies areas not people.</div>
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<b>When are you going to expand this to include my team?</b></div>
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I'm not planning to, but I'm sure it would be even more interesting than the Premier League.<br />
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<b>Curiosities</b><br />
On all the maps, north is up so I couldn't help notice that Manchester United seem to be the only team playing on an east to west pitch. I'm guessing most grounds don't do this so that they can avoid the setting sun problem - and in fact Old Trafford cricket ground rotated their pitch 90 degrees to avoid this problem <a href="http://news.bbc.co.uk/local/manchester/hi/people_and_places/newsid_9066000/9066829.stm" target="_blank">in 2010</a>. Shades of blue - representing the 40% least deprived areas - appear on only 7 of the maps, and only two grounds are in such areas. Red (20% most deprived areas) appear on 19 maps - only Watford is the exception. The maps for Everton, Man City, Tottenham and West Brom are entirely red - which indicates that these grounds and surrounding areas (a few hundred metres in each direction) are within wider areas classified as the most deprived in England. The very most deprived areas to appear on any of the maps are ranked 24 (beside Goodison) and 29 (beside Anfield). </div>
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<b>Which team do you support?</b></div>
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ICTFC, of course. But not very enthusiastically. </div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-60002897579439287932015-10-28T23:43:00.000+00:002015-10-29T08:53:26.176+00:00Mapping property conditions in Detroit<div style="text-align: justify;">
I've written here a <a href="http://www.undertheraedar.com/2009/12/plan-to-save-detroit.html" target="_blank">couple</a> of <a href="http://www.undertheraedar.com/2014/07/mapping-blight-in-motor-city.html" target="_blank">times</a> before about Detroit, in relation to my family history and my interest from a data/urban point of view. Last year I did a short piece on the amazing <a href="https://www.motorcitymapping.org/" target="_blank">Motor City Mapping </a>project, a comprehensive effort to digitize the city's property information and provide clear data which can help the city move forward. In the first phase of the project 150 Detroiters surveyed the entire city (about 380,000 land parcels) and this information was used in the Blight Elimination Task Force's report. You can read more about all this <a href="https://www.motorcitymapping.org/about" target="_blank">here</a>. This post is about mapping the results of their work and property conditions in particular. Properties are categorised as being in 'good', 'fair', or 'poor' condition, or else demolition is suggested. I mapped this for all 54 of the city's neighbourhoods, as in the image below.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiKv3JkdY_EJCGLuEuBJSnoLt-MVAOGCPugtcszieNDHQk6ktAbE8nQvC4kX3MdmORFb87pE75Gvtuvvzbm8kb7ziN2XlMxes7MxSsMeA8r0PhZg2j5_C5d33iiZER_8Y9YZ6LAwv9dXvs/s1600/NHOOD_36_MCM_2014.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiKv3JkdY_EJCGLuEuBJSnoLt-MVAOGCPugtcszieNDHQk6ktAbE8nQvC4kX3MdmORFb87pE75Gvtuvvzbm8kb7ziN2XlMxes7MxSsMeA8r0PhZg2j5_C5d33iiZER_8Y9YZ6LAwv9dXvs/s320/NHOOD_36_MCM_2014.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">One of the 54 maps I created for the City of Detroit</td></tr>
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The 'neighbourhoods' I used are the 54 'Master Plan Neighborhoods' provided by Data Driven Detroit, and available <a href="http://portal.datadrivendetroit.org/datasets/a25b7114d233496eaece59a23e31f4b2_0" target="_blank">here</a> as open data. For each area I've shown the proportion of properties in each category, in addition to the total number of structures for each area. The image above shows the Mt. Olivet neighbourhood to the north of the city, whereas the map below shows Chadsey, to the south of the city. One of the points I wanted to make here is that although Detroit has its problems - well documented - it's not necessarily the burning relic that some portray it to be. Anyone looking for an insight into all of this would do well to listen to fifth generation Detroiter George Galster's <a href="https://www.youtube.com/watch?v=JBrNmouPE2I" target="_blank">Driving Detroit lecture</a> (which he also gave here in Sheffield last year).</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUMuH_Mw6Slplr_cM5yB969jRgjwYNOzRn6H7RZMwLdeTt-kRpdzLB1fGRP6ZYt1kyu2xhCcQq65Bs7g7ke2PHa-WcyTYoO_U7wA04aMqY9rN24-hswE2dcty5vGdsFq8TsFD45t2IvQc/s1600/NHOOD_10_MCM_2014.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUMuH_Mw6Slplr_cM5yB969jRgjwYNOzRn6H7RZMwLdeTt-kRpdzLB1fGRP6ZYt1kyu2xhCcQq65Bs7g7ke2PHa-WcyTYoO_U7wA04aMqY9rN24-hswE2dcty5vGdsFq8TsFD45t2IvQc/s320/NHOOD_10_MCM_2014.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Detroit is mostly 'good' - see, it's not so bad!</td></tr>
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The other reason that I'm returning to the topic is because I teach using this fantastic dataset. It's fascinating in itself but it's also a great example of how cities can create, and then use, open data to help turn things around - or at least begin to. Half the battle is knowing where to start and the Motor City Mapping project provided a solid base for this.</div>
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My family history has always been tied to Detroit and although I've never lived there every time I've visited I liked what I saw and the people were really friendly. I'm probably biased but aren't we all? Last winter I found a few pieces of Detroit history in the family archives, which I'll share here as they are a little slice of the city that no longer exists. First, one of my grandparents' wedding photos, from late 1929, then a description of the event from a Scottish paper - followed by a photo of the Danish Brotherhood Hall mentioned in the piece. </div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRz3k_EvJG2YkLwFa8CkpQcFAkmSdsNyubiTYol1flQdf9CEZRzxpT7IU06T3Ubk4XtbGmJfzNTq9tSA_MOyrM46scEC6sizM1YKTDRfmV079frWjAQHc9DD1NnX1G39AqQVU7T1zYcUg/s1600/detroit_wedding.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjRz3k_EvJG2YkLwFa8CkpQcFAkmSdsNyubiTYol1flQdf9CEZRzxpT7IU06T3Ubk4XtbGmJfzNTq9tSA_MOyrM46scEC6sizM1YKTDRfmV079frWjAQHc9DD1NnX1G39AqQVU7T1zYcUg/s320/detroit_wedding.jpg" width="240" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">1920s style!</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWNOgkQ9wIUcZtnPM3BxVHkNRVw8Cf_e9_-MBtWb6j62IhLUq0dMvk2O_4LlzlJ0qinryAR2azm6xqc2QRoRuCTiSUIDtT_A6aBWBmjMP-lCcvrRxg8dd-inTRetWuz75BeDnmFQQj4cs/s1600/detroit_wedding_2.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWNOgkQ9wIUcZtnPM3BxVHkNRVw8Cf_e9_-MBtWb6j62IhLUq0dMvk2O_4LlzlJ0qinryAR2azm6xqc2QRoRuCTiSUIDtT_A6aBWBmjMP-lCcvrRxg8dd-inTRetWuz75BeDnmFQQj4cs/s320/detroit_wedding_2.jpg" width="240" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Yes, they had Comic Sans in 1929...</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhhUrOuztEPP9TbiWvYfTRi_KGCLz0x0EbwJBHc3t0kpqXyAwbEhKO_NACKVnVUbL-SfGhritBfZ-EOIq7y9rPP4Wo4hUl84PNcWTO0AnX3QN2BbgphG0_p8YSCrVBFeu_Bv2-4_AjwVI/s1600/danish_brotherhood.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="253" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhhUrOuztEPP9TbiWvYfTRi_KGCLz0x0EbwJBHc3t0kpqXyAwbEhKO_NACKVnVUbL-SfGhritBfZ-EOIq7y9rPP4Wo4hUl84PNcWTO0AnX3QN2BbgphG0_p8YSCrVBFeu_Bv2-4_AjwVI/s320/danish_brotherhood.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The 'Danish Brotherhood Hall'</td></tr>
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Note in the image above of the Danish Brotherhood Hall a Danish flag has actually been painted over and if you look at it on <a href="https://t.co/Z7he5wZzkl" target="_blank">Google Street View</a> you can see the 'DB' inscription on the building's upper centre section. Detroit Urbex published a really <a href="http://www.detroiturbex.com/content/churches/stunfaithful/index.html" target="_blank">fascinating history</a> of this building, which is well worth a read. Anyway, it's interesting for me that the story of Detroit, as it were, is also wrapped up a little bit in my family history and can be seen in the images associated with my grandparents' wedding.</div>
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Back to the maps - <a href="https://drive.google.com/folderview?id=0B0kRhiw4fD7uUEp2QUgtQXJfZUk&usp=sharing" target="_blank">I've shared them all via Google Drive</a> so that anyone can access them and use then if they so wish. </div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiEcG1OEB9fCwHPeN3m7acfWm7oc_dzouZYGVSBAckA1MjQL6ghSLwxFGCqS58NP9Vl8njKmNBM-30MWgzL8Usk8x8VneXdcjF8ICtHgYl-UZLEUHXLzIagKLmUqElrdKhqP3fXlFkowmk/s1600/mcm.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="251" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiEcG1OEB9fCwHPeN3m7acfWm7oc_dzouZYGVSBAckA1MjQL6ghSLwxFGCqS58NP9Vl8njKmNBM-30MWgzL8Usk8x8VneXdcjF8ICtHgYl-UZLEUHXLzIagKLmUqElrdKhqP3fXlFkowmk/s320/mcm.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Property condition maps for all 54 neighborhoods</td></tr>
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The only other thing to say is that if you download the <a href="http://d3.d3.opendata.arcgis.com/datasets/80f30d7f6683441cacef62574a22d8a9_0" target="_blank">original dataset</a> you'll see that each land parcel also has a URL with a photo of it - quite an achievement when you realise there are nearly 380,000 of them. </div>
Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-42489081982694301402015-10-18T08:07:00.000+01:002015-10-18T20:31:20.058+01:00Glowing lines in QGIS<div style="text-align: justify;">
In one of <a href="http://www.undertheraedar.com/2014/10/flow-mapping-with-qgis.html" target="_blank">my previous QGIS posts</a>, on flow mapping, I outlined a method for mapping origin-destination data related to movements, rendered as a collection of straight lines from point a to b. One thing I didn't do in that post was explain how you get the 'glow' effect to make the lines appear brighter at higher densities (example below).<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjc4DWqSSodZCuBxG2r77vtP7cKb-ddDaUZ2JXYXgMXo2ePULNwlzMgZxk8T2jEP8s74rH3YTSuvj7Vkn9Vpjbmx23zOw2o2f1TGk20DkTqc6zGfJgliGdoQRHxZaWaVbZ3hyphenhyphenqA9myoVek/s1600/glow_qgis.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="212" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjc4DWqSSodZCuBxG2r77vtP7cKb-ddDaUZ2JXYXgMXo2ePULNwlzMgZxk8T2jEP8s74rH3YTSuvj7Vkn9Vpjbmx23zOw2o2f1TGk20DkTqc6zGfJgliGdoQRHxZaWaVbZ3hyphenhyphenqA9myoVek/s320/glow_qgis.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A little glowing flow map example from my US commuting map</td></tr>
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Since a few people have asked about it, I thought I'd share it - and thanks to <a href="http://nyalldawson.net/2013/03/coming-soon-in-qgis-2-0-blend-modes-for-layers/" target="_blank">Nyall Dawson</a> and all the other QGIS developers for making this possible. If I begin with a commuting flow dataset I made for England and Wales and just add it to QGIS, here's what I get (click on the individual images to see them full size):</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiRT7DMlSSa73Vu-0z9lZAQvRU7OuRkNwTPI0iFRgsf05L03BVJQcKozo08iI2Iy3a2tTbytX8-x3F7sAo8H55-_alrlesxdIkjSL2cck0OIKO1refe3k26u-qRk3aWiZjvOQjnaBUR3XM/s1600/raw_unblended_original_10%252B_ttw_ew.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiRT7DMlSSa73Vu-0z9lZAQvRU7OuRkNwTPI0iFRgsf05L03BVJQcKozo08iI2Iy3a2tTbytX8-x3F7sAo8H55-_alrlesxdIkjSL2cck0OIKO1refe3k26u-qRk3aWiZjvOQjnaBUR3XM/s320/raw_unblended_original_10%252B_ttw_ew.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">We can see the country outline, that's about it</td></tr>
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Next, let's try reducing the default line width from 0.26 to 0.1 and see what happens...</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjMwHxJZFX30L4cuG6acbHT6vRtUGe8nVzU5RK-ZpPwIWsLSkZMUBAFs2gJVEb8BpPYjQGR5VtIcmWQyCH1S-4kJZ_SDSxJ1ENaY51gUgq0xrnsdDJmrkd5Kh3BVAvxTeLu9jvfp4mERp4/s1600/raw_unblended_original_10%252B_ttw_ew_0.1_width.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjMwHxJZFX30L4cuG6acbHT6vRtUGe8nVzU5RK-ZpPwIWsLSkZMUBAFs2gJVEb8BpPYjQGR5VtIcmWQyCH1S-4kJZ_SDSxJ1ENaY51gUgq0xrnsdDJmrkd5Kh3BVAvxTeLu9jvfp4mERp4/s320/raw_unblended_original_10%252B_ttw_ew_0.1_width.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">This is a bit clearer, but still not very useful.</td></tr>
</tbody></table>
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We could darken the background (via Project > Project Properties > General) to make the lines stand out more...</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV58MhZRfqdC-d3LXxbApAPudDRfGrDkwpNgI_oLtcqtvvd0iKG3c7GSDLH2s-9WFl7kunsp0-U4Zo2o2fxHRBSGEwl-3UAFYIZ-TfnYBncPeOkWNYRBCfrfowbSFuG6EH5LhN6Qgshpo/s1600/raw_unblended_original_10%252B_ttw_ew_0.1_width_black_background.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV58MhZRfqdC-d3LXxbApAPudDRfGrDkwpNgI_oLtcqtvvd0iKG3c7GSDLH2s-9WFl7kunsp0-U4Zo2o2fxHRBSGEwl-3UAFYIZ-TfnYBncPeOkWNYRBCfrfowbSFuG6EH5LhN6Qgshpo/s320/raw_unblended_original_10%252B_ttw_ew_0.1_width_black_background.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">This is getting a bit better now, but still not great</td></tr>
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Okay, let's now change the colour and introduce some feature transparency and see how this looks:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjufFCF4xmKG4bQs1zoZgJJMJpZqrW9csRx8QqdcnTy4xMI7tSkKtV9Co_i6bC8jQef1kRcNPFUp8SlVG2KaKe-scQdbq061iP9VC-z9q5ZTwZcH0LUk2nAmXeAcuiYdgTU2JNqFk-fV9c/s1600/blue_10%252B_ttw_ew_0.1_width_black_background.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjufFCF4xmKG4bQs1zoZgJJMJpZqrW9csRx8QqdcnTy4xMI7tSkKtV9Co_i6bC8jQef1kRcNPFUp8SlVG2KaKe-scQdbq061iP9VC-z9q5ZTwZcH0LUk2nAmXeAcuiYdgTU2JNqFk-fV9c/s320/blue_10%252B_ttw_ew_0.1_width_black_background.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Definitely an improvement, but not great</td></tr>
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Note how this was done, if you don't already know:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQZXPeK_60yGG6uiKflAdlPOVfdUOOsIpp8H9b5-uc-edplxga4CRigVit1XnFavrCwvgPULf_AB8NcmPcR1QStOAFFtMmHigdqY1slM5WewYjGdsL6XBfoj5ErG-9CIUD0clICTP0Dzc/s1600/blue_90%2525_transparent.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="225" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQZXPeK_60yGG6uiKflAdlPOVfdUOOsIpp8H9b5-uc-edplxga4CRigVit1XnFavrCwvgPULf_AB8NcmPcR1QStOAFFtMmHigdqY1slM5WewYjGdsL6XBfoj5ErG-9CIUD0clICTP0Dzc/s320/blue_90%2525_transparent.png" width="320" /></a></div>
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So far, so good. But what about the glow effects? That's where feature blending mode comes in - as you can see below:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsiffKcx9hiQQ6aKVFrBztFne151h-GPf_CNWF3-6FkHFX2V6bJqMur5zXk9RdNp5RVF938IPG1q-DFTXK18K31dbEvdNtsL-V-xfdKr-7YYMAcxWWV6Yrs8SuLBp8KGCBnJgMoJDyDaE/s1600/feature_blend_options.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="248" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsiffKcx9hiQQ6aKVFrBztFne151h-GPf_CNWF3-6FkHFX2V6bJqMur5zXk9RdNp5RVF938IPG1q-DFTXK18K31dbEvdNtsL-V-xfdKr-7YYMAcxWWV6Yrs8SuLBp8KGCBnJgMoJDyDaE/s320/feature_blend_options.png" width="320" /></a></div>
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With a line width of 0.1, transparency of 90% (because I have a couple of million lines here) and a Feature blending mode set to 'Addition' here's what I get:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhYQ_5P6oz6bVPFzWTdqfkU7rXhhbFb4C9jPyoCgGXT_Cb8WpnjowKHQLEdf8x0eR14QxGa37Jv4rk8puwFYxZQCoe93MU6rPljWLSMPQw2tY91jKKMVd4U2Up5wigRfuEYsDzgpiAx-88/s1600/blue_10%252B_ttw_ew_0.1_width_black_background_blend_addition.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhYQ_5P6oz6bVPFzWTdqfkU7rXhhbFb4C9jPyoCgGXT_Cb8WpnjowKHQLEdf8x0eR14QxGa37Jv4rk8puwFYxZQCoe93MU6rPljWLSMPQw2tY91jKKMVd4U2Up5wigRfuEYsDzgpiAx-88/s320/blue_10%252B_ttw_ew_0.1_width_black_background_blend_addition.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">You may need a different transparency % in your data</td></tr>
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What on earth do all the different blending modes do? There's 'Screen', 'Multiply', 'Dodge' and many more but it's not immediately obvious so here's a little summary from the <a href="https://docs.qgis.org/2.8/en/docs/user_manual/working_with_vector/vector_properties.html" target="_blank">QGIS 2.8 documentation </a>pages on the subject:</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhCdtUc1cW9Co6FT4pfk1QrHoRtDQZUmMplykzp0j7rFsXXZTmOdLHCP2hfkOVYLRTLFBfY0Y2k8fztWfVwuSrP4r6yKzlDYv9IpgRr_3ZjfEVRvcWXOMFekZnk-KsBwahyphenhyphenePmEp7Yhj3E/s1600/layer_rendering.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhCdtUc1cW9Co6FT4pfk1QrHoRtDQZUmMplykzp0j7rFsXXZTmOdLHCP2hfkOVYLRTLFBfY0Y2k8fztWfVwuSrP4r6yKzlDYv9IpgRr_3ZjfEVRvcWXOMFekZnk-KsBwahyphenhyphenePmEp7Yhj3E/s320/layer_rendering.png" width="233" /></a></div>
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To see the different impact each feature blending mode has, it's best to try them - for example, if you want a less 'glowy' version of the previous example above, you could used 'Dodge', as shown below:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgR0TN9yEeRkaLXpIuCMuP443m7LnlaivPc7QXr3NjHJ2ND9kKLvEyGc6dsn9zvsirssYilWW6s83zPAu34GUOIMRLxK8n0hwM05UMm4u3UEnATbTfFhDX76x4DUTIlwtHyvf39JHk4q_0/s1600/blue_10%252B_ttw_ew_0.1_width_black_background_blend_dodge.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgR0TN9yEeRkaLXpIuCMuP443m7LnlaivPc7QXr3NjHJ2ND9kKLvEyGc6dsn9zvsirssYilWW6s83zPAu34GUOIMRLxK8n0hwM05UMm4u3UEnATbTfFhDX76x4DUTIlwtHyvf39JHk4q_0/s320/blue_10%252B_ttw_ew_0.1_width_black_background_blend_dodge.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Similar to the previous one, but this is 'Dodge'</td></tr>
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Of course, you could also decide that you want the lines to be different colours and symbolise them differently based on their length. With this, you take a different approach and it would look something like the image below, where I've used reds:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjz241tYpCNMY_-EapBwB7Y3kjkMMny_1cRLaALwtHYh8q4WZLGOYSg4fGL6UF2PNNbqSWOUiFt_U3zK8zDMBHLKVvOVxL_fn-jrazrY5PqiL2j63hYtgG2WKv9DTp0YosLnzybMufAACQ/s1600/reds_symbol_levels_10%252B.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjz241tYpCNMY_-EapBwB7Y3kjkMMny_1cRLaALwtHYh8q4WZLGOYSg4fGL6UF2PNNbqSWOUiFt_U3zK8zDMBHLKVvOVxL_fn-jrazrY5PqiL2j63hYtgG2WKv9DTp0YosLnzybMufAACQ/s320/reds_symbol_levels_10%252B.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">No feature blending here, just layer symbology and ordering</td></tr>
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To achieve the above, you'd have to have a line length field (but that's <a href="http://www.qgistutorials.com/en/docs/calculating_line_lengths.html" target="_blank">easy</a> in QGIS) and then color different lengths slightly differently and then use layer ordering. This too requires a good bit of experimenting to get right (and the ones shown here are far from perfect examples) but here's an example from the layer properties dialogue:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhu7EwLCUOxzCVYPWYyUgrKkrfm7nsQwDUP3WPsKW9jWzIXNbPFNGJvOCzfab9WhN-lWC01nuck2ZArTEY9MIM_YP8O8R0ZYLj-67Dui1lsf3T93KlsvukzT29tTgFRSaIKW3OTw5p1z5c/s1600/reds_symbol_levels.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="198" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhu7EwLCUOxzCVYPWYyUgrKkrfm7nsQwDUP3WPsKW9jWzIXNbPFNGJvOCzfab9WhN-lWC01nuck2ZArTEY9MIM_YP8O8R0ZYLj-67Dui1lsf3T93KlsvukzT29tTgFRSaIKW3OTw5p1z5c/s320/reds_symbol_levels.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Note: click 'Advanced' to see symbol levels</td></tr>
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The only other thing to mention is that when you zoom in you'll see things differently and perhaps need to change the symbology to suit the zoom level. You can see this for the example below where I've zoomed in to London and changed the transparency down to 70%:</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgi-MggpZVqg-VkMFvx4BMm_fd_7E-t1iBPXXDg1tmichhSsqh5iwTFD5ygUoLjdkdP8sbgrAqsgI24DGOVfSufkLV9eBtA1A7fLp9DevQ3hhNqzTimXv5EWboA2Vic5yreL_QI0DSx4U/s1600/reds_symbol_levels_10%252B_zoomed_now_70%2525_trans.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="167" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgi-MggpZVqg-VkMFvx4BMm_fd_7E-t1iBPXXDg1tmichhSsqh5iwTFD5ygUoLjdkdP8sbgrAqsgI24DGOVfSufkLV9eBtA1A7fLp9DevQ3hhNqzTimXv5EWboA2Vic5yreL_QI0DSx4U/s320/reds_symbol_levels_10%252B_zoomed_now_70%2525_trans.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Now we can begin to make more sense of the flows</td></tr>
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If you want to know how to create the flow lines in the first place, check out my previous post on the subject, where I also provide a <a href="http://www.undertheraedar.com/2014/10/flow-mapping-with-qgis.html" target="_blank">sample dataset</a> to work with. Once you've got things looking as you want them, you can then add labels and all sorts of other things to make your map more informative. Note that I used QGIS 2.10 here but this should work from QGIS 2.2 and above.</div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-9794646798284986112015-10-01T22:49:00.001+01:002015-10-02T16:25:31.640+01:00Are map legends too lazy?<div style="text-align: justify;">
A somewhat click-baity blog title, but I wanted to crowdsource some knowledge from proper carto/viz people, so if you have any insights on what I write, please feel free to get in touch <a href="https://twitter.com/undertheraedar" target="_blank">via twitter</a> or <a href="http://www.sheffield.ac.uk/usp/staff/alasdair_rae" target="_blank">e-mail</a>. No doubt what I write about below already has a name but I don't know what that is and I haven't seen this functionality in proprietary or open source GIS. By asking 'are map legends too lazy', what I really mean is are GIS-made choropleth map legends doing enough for us in their current form - and is there an opportunity for us to add some new functionality which enhances the communicative power of the humble choropleth legend? An example... look at the map below, which I created in QGIS. It's a map of a new deprivation* dataset for England, focused on the local authority of Birmingham.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgqSBYHi30OPxJZslBwY_djinJ0_b5pAqXYUZfvnp_JMX1fpopRAAZDzeBRrvkXghtLkgMI7mRq4ClkItYDqti36ibF-GvRjI2D8Op3Z2dciyU8uzAgAnAugqRN6JL-93GrgtsVw3_g1rY/s1600/imd2015_Birmingham.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgqSBYHi30OPxJZslBwY_djinJ0_b5pAqXYUZfvnp_JMX1fpopRAAZDzeBRrvkXghtLkgMI7mRq4ClkItYDqti36ibF-GvRjI2D8Op3Z2dciyU8uzAgAnAugqRN6JL-93GrgtsVw3_g1rY/s320/imd2015_Birmingham.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Deprivation choropleth, with legend and inset map</td></tr>
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This dataset is typically understood and discussed in terms of deciles, hence the classification used above. The dataset goes from decile 1 (most deprived) to decile 10 (least deprived) - within the context of England as a whole. Cities like Birmingham tend to have a higher proportion of their small areas in the most deprived decile, and in map form this results in lots of red and not much blue, as you can see above. If you wanted to find out how many areas were in decile 1 (most deprived) you would know that it was 'a lot' but because the inner-urban areas tend to be smaller in size (relative to the blue ones), making an accurate assessment visually is quite difficult. In fact, owing to the different sizes of the spatial units, you could quite easily take the wrong message away from a choropleth like this.</div>
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<b>My solution? Make the legend do more work.</b> Make it tell us not just what the colours represent but also what proportion of areas are in each category by scaling the colour patches relative to the proportion of areas in each choropleth class - in the form of a bar chart - what I call a '<a href="http://www.undertheraedar.com/2015/05/the-2015-general-election-london-results.html" target="_blank">bargend</a>' (jump in at this point if you already have a name for this). You could, without much effort, add in a table or a separate chart, but I want the legend to actually <i>be</i> the bar chart. In part, I was inspired to attempt this in QGIS because of Andy Tice's <a href="https://www.flickr.com/photos/97267218@N06/16314288595/" target="_blank">prototype scatterplot layout</a> and his comment that he'd like to get it working in the QGIS Atlas tool. Here are some results, followed by further thoughts.<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6PQcAE9mdaa3l4H3MA7B8ezsVqwosF7qDiAY6GqI0spDpGQsokbsVVFKvKdwOQFG-mSxgb_VU8MhP7e1HY0ZPNTb5qnZrDeFMlJmnAH1G6Lke8wJiw5LqKZEWLrHPn8_CGF6JH7sBG-w/s1600/imd2015_Birmingham.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg6PQcAE9mdaa3l4H3MA7B8ezsVqwosF7qDiAY6GqI0spDpGQsokbsVVFKvKdwOQFG-mSxgb_VU8MhP7e1HY0ZPNTb5qnZrDeFMlJmnAH1G6Lke8wJiw5LqKZEWLrHPn8_CGF6JH7sBG-w/s320/imd2015_Birmingham.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">This time, I've added in a 'bargend'</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgZdDW9LfLxsbVASMhTTN3sx3-uxoa5wQFKcB-tmIFrkmIxKh7lvIVuCxBE9Xrh8iSNXatNkq322585mXUG_nwGkwZlBtjvaEoj3wUzMq8HmrYgOV4zVLyDxBBmzIQHd4yfzSBPDVT6XTQ/s1600/bargend.png" imageanchor="1" style="margin-left: auto; margin-right: auto; text-align: center;"><img border="0" height="305" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgZdDW9LfLxsbVASMhTTN3sx3-uxoa5wQFKcB-tmIFrkmIxKh7lvIVuCxBE9Xrh8iSNXatNkq322585mXUG_nwGkwZlBtjvaEoj3wUzMq8HmrYgOV4zVLyDxBBmzIQHd4yfzSBPDVT6XTQ/s320/bargend.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A closer look at the bargend for Birmingham</td></tr>
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When I do a visual comparison of the Birmingham map, I'm surprised that the least deprived (i.e. richest) areas only account for 1.7% of the total, because I'm drawn to the blue of the choropleth. This could be solved though a cartogram approach, but I wanted to preserve geographical accuracy here. I'm not surprised that almost 40% of areas are in the poorest decile - that's what I'd expect from <a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=1_voj0kAAAAJ&citation_for_view=1_voj0kAAAAJ:9yKSN-GCB0IC" target="_blank">what I know</a> about deprivation in English inner-cities. Let's look at another example below.<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhh2T0p29q_v2mJO9lIqud6TNPNCNOghwW3wJYCwmETP34hPRf4_p64hDsVP0fIVQeW9WefbXp9YiBTbVnmd8rAgbKHRrxSlB5srsH7aXDlJJP72dfgiIY-wRdUh4wb8o9pR_2PQ4zzCE0/s1600/imd2015_Tower+Hamlets.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhh2T0p29q_v2mJO9lIqud6TNPNCNOghwW3wJYCwmETP34hPRf4_p64hDsVP0fIVQeW9WefbXp9YiBTbVnmd8rAgbKHRrxSlB5srsH7aXDlJJP72dfgiIY-wRdUh4wb8o9pR_2PQ4zzCE0/s320/imd2015_Tower+Hamlets.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The London Borough of Tower Hamlets</td></tr>
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This time I've shown one of the poorest parts of London - Tower Hamlets. An interesting aside here is the emergence of one area in decile 9 (i.e. richer area) compared to the pattern from 2010. This is almost certainly linked to gentrification and displacement rather than individuals becoming 'less deprived'. I find the extra information provided in the bargend very useful analytically/cognitively compared to the simple legend we would normally use.<br />
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Now let's look at a few more...<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUK4prGqvz7fc8pQVcD14BSXxzNJB7PchIsRBaJTnirIE7w24KE1KvmS9OQAGQfP079wTogbeS55jQhz5iIjprGYEDc7T08K3u_LROIgqJ9tFEH0WRilxo7gQ5stR2QVhrYGqd4ABOrOo/s1600/imd2015_Liverpool.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUK4prGqvz7fc8pQVcD14BSXxzNJB7PchIsRBaJTnirIE7w24KE1KvmS9OQAGQfP079wTogbeS55jQhz5iIjprGYEDc7T08K3u_LROIgqJ9tFEH0WRilxo7gQ5stR2QVhrYGqd4ABOrOo/s320/imd2015_Liverpool.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Liverpool contains relatively few 'non-deprived' areas</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhVaS8OmnpDzHDR8PJQr06sn5CMhMsNWq7VWdLN271gDNvRK8aOGB6hln19fP8Y0KaQ05CCto3gk5q3121D7kW5atyh_9YecZs0tPAZUb-1O0aN8tM8T9EZeP0g5fiwqzIT_S5N3K4SYq4/s1600/imd2015_Manchester.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhVaS8OmnpDzHDR8PJQr06sn5CMhMsNWq7VWdLN271gDNvRK8aOGB6hln19fP8Y0KaQ05CCto3gk5q3121D7kW5atyh_9YecZs0tPAZUb-1O0aN8tM8T9EZeP0g5fiwqzIT_S5N3K4SYq4/s320/imd2015_Manchester.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Like Liverpool, Manchester has many poor areas</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5yv7noM3y_8dBqvkjPgxNAzGCP_AhJDje1J6mz5qEqCbG_jkNEmXV6AZZAJGVAWe7dc8iXEZLAFWSaTp1o5sKmcl1DZED1nr3DkY0MeVcSDSa_R-4bw3l0GsMxN9HmEQmSIAIo9nZqbY/s1600/imd2015_Middlesbrough.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj5yv7noM3y_8dBqvkjPgxNAzGCP_AhJDje1J6mz5qEqCbG_jkNEmXV6AZZAJGVAWe7dc8iXEZLAFWSaTp1o5sKmcl1DZED1nr3DkY0MeVcSDSa_R-4bw3l0GsMxN9HmEQmSIAIo9nZqbY/s320/imd2015_Middlesbrough.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Middlesbrough has the highest % in the most deprived decile</td></tr>
</tbody></table>
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One of the benefits of this approach, in my view, is when you compare different places - you can click on an image above and then go forward and backward to make comparisons. The added value of the bargend approach means that you have precise details of the proportion of areas in each decile and you can make more meaningful comparisons. You could just do this with a table or chart and dispense with the map altogether, but then you'd lose the very important ability to identify where precisely individual areas are and where spatial concentrations of deprivation (and affluence) exist. Talking of affluence, it's only fair that I show you some maps of places that are at the opposite end of the scale. Two prime examples...<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjcWS0eSBoXJpyaU77CzWT-y6-jpNFLOQNObchorSMDF111nCxOx0A_L9jRni-t5l9gK-49KWFyOq0Fl6bVvoubcrqSJ_mdK2KcU7yJdTHVezk9xIWYG2X1_qETNJJjPVnsJaj_Be_I8Ss/s1600/imd2015_Surrey+Heath.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjcWS0eSBoXJpyaU77CzWT-y6-jpNFLOQNObchorSMDF111nCxOx0A_L9jRni-t5l9gK-49KWFyOq0Fl6bVvoubcrqSJ_mdK2KcU7yJdTHVezk9xIWYG2X1_qETNJJjPVnsJaj_Be_I8Ss/s320/imd2015_Surrey+Heath.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A beautiful part of the world, but very blue</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJJXH_w91d9Zb91h_wLImAi8pwAR288QOs4m64D_9OCsKh2iyMlV8a8coxAC0hik0SE0ERFxzckzJd058gn2P7COI_rdgEBt5lltpsi6McrgmuxGgBir5Ty4viH5vDhhXQQMS5j0b0OSk/s1600/imd2015_Hart.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhJJXH_w91d9Zb91h_wLImAi8pwAR288QOs4m64D_9OCsKh2iyMlV8a8coxAC0hik0SE0ERFxzckzJd058gn2P7COI_rdgEBt5lltpsi6McrgmuxGgBir5Ty4viH5vDhhXQQMS5j0b0OSk/s320/imd2015_Hart.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Hart, you almost broke my chart (highest % in decile 10)</td></tr>
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I'll wrap up with a few points.<br />
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<b>1. </b>I'd love it if someone could find a way to add in this functionality natively in QGIS. I had to do a bit of thinking and tinkering to automate this in the Atlas tool, but I now have it working well and everything dynamically updates and re-positions itself once you set it up.<br />
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<b>2. </b>I wouldn't always want to use a bargend, but I think it's something that adds value without taking up much more space (if any) in map layouts.<br />
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<b>3.</b> I'm trying to think of any drawbacks of this approach, but I can't. I'm happy for others to chip in with ideas on this.<br />
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<b>4. </b>I think 'bargend' is a terrible word. Please tell me it already has a nice sounding name, or invent one for me.<span style="color: #666666;"> <span style="font-size: x-small;">[<b>update</b>: in my rush to coin a phrase, and because I was mapping deciles as categories - as in a bar chart - I was thinking about bar charts rather than histograms. This is really a histogram but it uses named categories (deciles) which in theory could be re-ordered and the chart would still make sense, so perhaps the bargend retains qualities of both and, anyway, a histogram still uses bars]</span></span><br />
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<b>5. </b><i>Are </i>map legends too lazy? Not really, but they can sometimes work harder.<br />
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<b>Addendum</b><br />
<a href="https://andrewpwheeler.wordpress.com/" target="_blank">Andrew Wheeler</a> very kindly got in touch to share <a href="http://www.citeulike.org/user/apwheele/tag/legend" target="_blank">a few relevant papers</a> on the subject. The Kumar paper is very close to what I propose (though he does the chart for the entire dataset rather than a subset) and he calls it a 'Frequency Histogram Legend' - more accurate perhaps, but less catchy. The Dykes et al. paper is very interesting and I like the treemap approach.<br />
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Hannes (<a href="https://twitter.com/cartocalypse" target="_blank">@cartocalypse</a>) also got in touch to say he likes the idea and he's suggested 'legumns', which is also useful (but more difficult to pronounce!).<br />
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I'll add more on the topic if people respond.<br />
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<span style="font-size: x-small;">* Just in case the use of this word sounds odd to you, we use the word 'deprivation' in the British context in studies of urban poverty/disadvantage but it's not exactly the same thing. I've written about this in previous academic papers but to all intents and purposes more deprived means 'poorer' and less deprived means 'richer'. In the maps above, you could say red: poor and blue: rich and you wouldn't be wrong (ecological fallacies notwithstanding).</span></div>
Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-87486713504841496272015-09-14T22:16:00.002+01:002015-09-14T22:21:25.561+01:00The Shapes of Cities<div style="text-align: justify;">
For a long time, I've been interested in the shape of cities and I suspect that if you're reading this you might be similarly afflicted. By 'shape' I mean their political boundaries as opposed to their general urban footprint. The latter can be seen by driving around or from a plane window, particularly when it's dark, but the political boundaries are much less obvious. This is particularly true of US cities. Take Houston, Texas - the first example below. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMe13hyIdSyO6Lk7T2mSsqwUwh-k60osYZ35sA0VF_p8z2WadOaPAIDn0hI4y60kTlLtV4PhUKRsz5kr5Vf_DEjCTXVVBEqSgUfF2IlZtMJZweHKZz0TBRE84BN5WMGSv6bXLUfRJSKDo/s1600/houston.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="265" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMe13hyIdSyO6Lk7T2mSsqwUwh-k60osYZ35sA0VF_p8z2WadOaPAIDn0hI4y60kTlLtV4PhUKRsz5kr5Vf_DEjCTXVVBEqSgUfF2IlZtMJZweHKZz0TBRE84BN5WMGSv6bXLUfRJSKDo/s320/houston.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The boundary of the City of Houston - <a href="https://www.google.co.uk/maps/place/Houston,+TX,+USA/@29.817178,-95.4012915,10z/data=!3m1!4b1!4m2!3m1!1s0x8640b8b4488d8501:0xca0d02def365053b" target="_blank">Google Map</a></td></tr>
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Look closely at this and - at least if you're not used to the political geography of American cities - you might be very confused by this fragmented, segmented mess of boundaries. Then go to Google maps and try different search terms, such as 'city of los angeles' or 'city of columbus' (Ohio) and you'll soon discover that Houston isn't that unusual at all. Try it for other cities and you'll see what I mean. Columbus, Ohio is a particular favourite of mine as I know it quite well having lived there for a couple of years in the early 2000s.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV8zpIklAUNSxkZ9_jkdkLLp3VftT47ivdryeWFCziWx5taSRbJobrLViJqUssAQR99f9MsZNBnAiUMkbx3mLKt6Qnm9f-dr1hsGRoHTgt4gvFaYjfOUvgP201ijnMDL1kTC8bUaqgNGs/s1600/los_angeles.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhV8zpIklAUNSxkZ9_jkdkLLp3VftT47ivdryeWFCziWx5taSRbJobrLViJqUssAQR99f9MsZNBnAiUMkbx3mLKt6Qnm9f-dr1hsGRoHTgt4gvFaYjfOUvgP201ijnMDL1kTC8bUaqgNGs/s320/los_angeles.png" width="266" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">City of Los Angeles - <a href="https://www.google.co.uk/maps/place/Los+Angeles,+CA,+USA/data=!4m2!3m1!1s0x80c2c75ddc27da13:0xe22fdf6f254608f4?sa=X&ved=0CHAQ8gEwEmoVChMIz8SN0673xwIVw28UCh0TOA_Q" target="_blank">Google Map</a></td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhdIjKbogxmnKmgDHJDUOPx5cXYgFz-1O6661GZdmQVKnrpXJdH0lrilNHSszjlH0luUDmBFlcPDPD7jFalcPIHuUFvImB5vv4z241WmnJ9aAxlrSUzgnoQFyBakd5YYGczmjlGd3eLeOs/s1600/columbus.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="303" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhdIjKbogxmnKmgDHJDUOPx5cXYgFz-1O6661GZdmQVKnrpXJdH0lrilNHSszjlH0luUDmBFlcPDPD7jFalcPIHuUFvImB5vv4z241WmnJ9aAxlrSUzgnoQFyBakd5YYGczmjlGd3eLeOs/s320/columbus.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">City of Columbus (Ohio) - <a href="https://www.google.co.uk/maps/place/Columbus,+OH,+USA/@39.9829515,-82.990829,11z/data=!3m1!4b1!4m2!3m1!1s0x883889c1b990de71:0xe43266f8cfb1b533" target="_blank">Google Map</a></td></tr>
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These unnatural-looking boundaries are the result of a complex mix of geography, history and politics that have real impacts on the ground. From education and transport to housing and waste management, the shapes of cities really do matter in this respect. Of course, this is a <a href="https://scholar.google.co.uk/scholar?q=underbounded+city&btnG=&hl=en&as_sdt=0%2C5" target="_blank">much-studied</a> topic in urban studies, not least by Professor John Parr of the University of Glasgow. In Parr's <a href="http://pascal.iseg.utl.pt/~depeco/sem0506/ft-0506-jparr.pdf" target="_blank">economic definitions of the city</a>, he outlines four types - but none of these explain the kinds of boundaries we see above. One major explanatory factor in all of this, of course, is tax revenue. But I'm not going to get into that now because it opens up a whole range of other topics, including white flight, suburbanisation, and schooling, amongst other things. The point is that the 'shapes' of cities are not accidental and who is included or excluded is inherently political. </div>
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In the United Kingdom, we might not have such unusual city boundaries, but the political geography of our cities is far from perfect - perhaps one reason for the resurgence of the 'city-region' concept over the past decade or so. When we're talking about urban economies, it makes much more sense to think about the <a href="http://www.undertheraedar.com/2015/07/mapping-polycentric-metrpololis.html" target="_blank">functional urban area</a> than it does to use data associated with an arbitrary political shape. This is as true in the US as it is in the UK. The example below shows that the City of Atlanta has less people than the City of Liverpool and that it's only slightly bigger in scale. But anyone who knows anything about these places will understand that 'Atlanta' is much bigger than 'Liverpool and is vastly more sprawling, with a metropolitan population of around 5.5 million compared to less than a million in 'Liverpool' (by one definition). </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8d7Fp3LnaiEFglc2fRdHU7V3T2hPaqr5p66DY8cV_9JmAkiVzjEQRMnnN-OtZntNE_K5NTxsiyEIJiMQQv8stMaz9RESWz_JfYlrkV0SY0uhNORILs6Nj9BY-WVQ8GG8l79Z_3JNwgXI/s1600/atl-liv.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="195" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj8d7Fp3LnaiEFglc2fRdHU7V3T2hPaqr5p66DY8cV_9JmAkiVzjEQRMnnN-OtZntNE_K5NTxsiyEIJiMQQv8stMaz9RESWz_JfYlrkV0SY0uhNORILs6Nj9BY-WVQ8GG8l79Z_3JNwgXI/s320/atl-liv.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Atlanta vs Liverpool - which is bigger?</td></tr>
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These kinds of issues are part of the reason organisations like the <a href="http://www.centreforcities.org/puas/" target="_blank">Centre for Cities</a> use the Primary Urban Area definition of cities for the 64 largest urban areas of the UK. In a recent study, I used a definition developed by <a href="http://geolytix.co.uk/" target="_blank">Geolytix</a> which is based on the 'sprawl' of the urban area rather than political boundary and found this to be a much better fit than the administrative area. When conducting comparative analyses of cities, we need to ensure we are comparing like with like, and using a functional definition often helps avoid the kinds of underbounded/overbounded problems that arise when (e.g.) comparing places like Manchester and Leeds. The former is normally said to be 'underbounded' because the functional urban area is much bigger than the local authority area of the same name and the latter is said to be 'overbounded' because of its much wider local authority area, which extends beyond the core urban fabric. For a comparison of UK 'city' sizes, see this graphic I produced a few years ago:</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgG7fx51JBTAthaN6FwIRuLO4DSeqx-t_P0JyETTEafM7X0aUuw0O_jKDhEIlN0LtWcIe8HG7p8sheH_6hrEMpJ33eP3gIrCrejkgbfyfuDBX-rD6X5AS11SEJOxqeVw-xKU_3GkiTOrr4/s1600/uk_city_size_grey.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgG7fx51JBTAthaN6FwIRuLO4DSeqx-t_P0JyETTEafM7X0aUuw0O_jKDhEIlN0LtWcIe8HG7p8sheH_6hrEMpJ33eP3gIrCrejkgbfyfuDBX-rD6X5AS11SEJOxqeVw-xKU_3GkiTOrr4/s1600/uk_city_size_grey.png" width="316" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">All cities shown at the same scale</td></tr>
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Surely there's a point to all of this? </div>
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Yes, glad you asked...</div>
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For planners, politicians, residents and neighbours, the shapes of cities matter enormously. It might dictate which school your children can go to, whether your local facilities are well funded, whether you have a well-functioning local transport system, when your bins get emptied, how many pot-holes you have in your street and all sorts of other things. But let's not get into that now. Instead, I'll end with another city shape, this time for the City of Detroit (one of my favourite cities, but much-maligned).</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgw1KzdUqnH5cLacVULzHz2g5LsNG6jaWVcGHe0Keu9gCP-tNKlJ1cmfNQ9ohD8gmUy1l6oI8H_McUp82cA8IBFm3QRE3uKpuBTBTR6gfOyYlIzKc2rhvr1XcVmAMFzhT-ejw1z7p3wJZA/s1600/detroit.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="208" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgw1KzdUqnH5cLacVULzHz2g5LsNG6jaWVcGHe0Keu9gCP-tNKlJ1cmfNQ9ohD8gmUy1l6oI8H_McUp82cA8IBFm3QRE3uKpuBTBTR6gfOyYlIzKc2rhvr1XcVmAMFzhT-ejw1z7p3wJZA/s320/detroit.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="https://www.google.co.uk/maps/place/Detroit,+MI,+USA/@42.3731896,-83.1078389,11.75z/data=!4m2!3m1!1s0x8824ca0110cb1d75:0x5776864e35b9c4d2" target="_blank">Detroit </a>- 8 mile boundary line to the north</td></tr>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-4971550587494201062015-09-10T21:43:00.001+01:002015-09-10T21:43:45.120+01:00From mega-regions to mega commutes: US commuting working paper<div style="text-align: justify;">
My <a href="http://www.undertheraedar.com/2015/08/mapping-american-commute.html" target="_blank">previous post</a> provided some images from a recent piece of work I did on mapping tract-to-tract commuting patterns in the contiguous United States. This post provides a bit more background and extracts from a <a href="http://eprints.whiterose.ac.uk/89361/7/WRRO_89361.pdf" target="_blank">working paper</a>, plus some of the original map outputs from the project - which are different in style (kind of a night time view). The focus is also more on mega commutes and mega-regions (think Gottmann's '<a href="https://en.wikipedia.org/wiki/Megalopolis_(city_type)" target="_blank">megalopolis</a>'). I also provide a bit more detail on the method and data.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNN_qkjNU0XG01bafCQz3JEqkoWiuP9rWdGvQFoObkHk9C01tb1Le0EARNTsfuJXvRgzUNeITN3zYGpdArwV4Zxk0OEK-q_IeR3LX_YYHWU1u7LtxGZ92d07GXXqBXmDQgg2mcGd0Ounk/s1600/mac1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="218" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNN_qkjNU0XG01bafCQz3JEqkoWiuP9rWdGvQFoObkHk9C01tb1Le0EARNTsfuJXvRgzUNeITN3zYGpdArwV4Zxk0OEK-q_IeR3LX_YYHWU1u7LtxGZ92d07GXXqBXmDQgg2mcGd0Ounk/s320/mac1.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A constellation of cities in the Midwest</td></tr>
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Being a member of the Regional Studies Association for a good few years now, I've followed various debates about regions, city-regions and mega-regions - including the very interesting work on mega-regions by the <a href="http://www.america2050.org/megaregions.html" target="_blank">America2050</a> project of the Regional Plan Association. I also have a longstanding interest in commuting flows (and mapping them) so I set myself the challenge of mapping micro-level commuting flows in the contiguous United States in the hope of identifying what I expected would be some interesting mega-region commutes. I also hoped, in the context of this data, that I would discover some of the mega commutes identified by <a href="http://www.census.gov/newsroom/releases/pdf/paper_mega_%20commuters_us.pdf" target="_blank">Rapino and Fields</a> of the US Census Bureau. On both counts I wasn't disappointed. The first map below shows the entirety of the lower 48 states and the commuting patterns come out quite clearly.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDU3CzfVaRy36GYeElozCea8G_jZXXiDQiDAggk31q3sYlVmRxgEX3IEscD2as47DfgXZ8-0ANldeD2lPfd24Ncsx3VKhMazApnGyF6VFKKLa6DXkQFkOo2W2e-gTUMPSy0CdllpjKacE/s1600/figure-1.tif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiDU3CzfVaRy36GYeElozCea8G_jZXXiDQiDAggk31q3sYlVmRxgEX3IEscD2as47DfgXZ8-0ANldeD2lPfd24Ncsx3VKhMazApnGyF6VFKKLa6DXkQFkOo2W2e-gTUMPSy0CdllpjKacE/s320/figure-1.tif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Journeys to work in the contiguous United States</td></tr>
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Obviously, some areas are more interesting than others, so I zoomed in on various areas, including California and the Northeastern United States. The map below shows travel to work patterns in California, and you can clearly see the wider Los Angeles metro area as one large commuter region, the Bay Area as another (but more <a href="http://www.wired.com/2015/08/pretty-maps-bay-area-hellish-commutes/" target="_blank">polycentric</a>), and also the settlement and journey to work patterns in the Central Valley, from Redding in the north down to Bakersfield in the South. This shows the urban settlement patterns in the state of California, but also the spatial configuration of the commuting connections between places.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsen9MchGIv_JwaDVuYHJBii93SIEIAu-F6Drf8I_r12bjem0zrHzUM7JU6mI1xm-HZHPq4yCYn6mbHVeqLupS3yThkqYirWW0Kc78PyGeVuVfqL8xU3yYch55W-rpHmnqmrY52TYW69s/s1600/figure-2.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgsen9MchGIv_JwaDVuYHJBii93SIEIAu-F6Drf8I_r12bjem0zrHzUM7JU6mI1xm-HZHPq4yCYn6mbHVeqLupS3yThkqYirWW0Kc78PyGeVuVfqL8xU3yYch55W-rpHmnqmrY52TYW69s/s320/figure-2.png" width="226" /></a></div>
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If you take a closer look at the working paper behind these maps you'll find out more about the data. What I found most interesting were the locations where 'mega commuting' was prevalent, so I looked at the top 20 Census tracts in the Northeastern US with the highest number of people commuting there - i.e. over 50 miles each way. As you can see from the table below, this is dominated by New York City, but Washington DC also features. The total volume may not seem much, but remember that these are quite small Census tracts, with only a few thousand people.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUFFeegafwRxYslC27Bil_62oleUGvp7FRLHR4s9M18-duURn0PS_wbp3vFgdRPR3NoLc5_TevfTVAZWkTVulZoeB7cTRazrHQlXIGiZ4HJrW5-VJAKEPP896OJ3SorXPVmZk1iYMULeI/s1600/table1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="233" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhUFFeegafwRxYslC27Bil_62oleUGvp7FRLHR4s9M18-duURn0PS_wbp3vFgdRPR3NoLc5_TevfTVAZWkTVulZoeB7cTRazrHQlXIGiZ4HJrW5-VJAKEPP896OJ3SorXPVmZk1iYMULeI/s320/table1.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Mega commuting in the Northeastern United States</td></tr>
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I then did something slightly different - I wanted to filter the data in a more scientific manner. Since the data provided by US Census Bureau includes a margin of error (MOE) value for each individual tract-to-tract flow, I calculated the coefficient of variation for each individual flow line (there were just over 4 million). These were based on a 90% confidence level, so the formula was simply:</div>
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((MOE/1.645)/Commuting Estimate) x 100</div>
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I used a rather generous cut-off and then displayed only those flows which had a coefficient of variation of less than 40. The results are shown in the map below. We can see the expected pattern of commuting but - hold on a minute - what are those really long distance lines? Surely people don't 'commute' vast distances like this. Well, it turns out that this might actually be true because many of these lines begin and end in military locations or other places associated with regular, long distance moves for work and since the American Community Survey asks respondents how they usually got to work ‘last week’, it's entirely plausible that a number of people will work away from home and that this will lead to the kinds of patterns we see below. Or, to put it another way, don't think of these long lines as journeys people travel every day! </div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJIBAJugpA9Nwq2bBsyAHHuxasFeosSTXXEJmwMRCPh8mbQXrQrPlPokB3FwUV3O96U2W0Dx_flXH-iZTizEv8cboAfTs8KoGBnotAB3fchFLwSc9BPziMZITJ_Wt49YBz2CqkWJwmwLQ/s1600/figure-6.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJIBAJugpA9Nwq2bBsyAHHuxasFeosSTXXEJmwMRCPh8mbQXrQrPlPokB3FwUV3O96U2W0Dx_flXH-iZTizEv8cboAfTs8KoGBnotAB3fchFLwSc9BPziMZITJ_Wt49YBz2CqkWJwmwLQ/s320/figure-6.png" width="320" /></a></div>
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If you want to read more about it, you can click below to see the working paper, which also includes links to high resolution versions of the images shown here.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgk7btmMwiHwXZdz6pz17ts_m3hWsS7716eUPX7cxR3G6_9MUNOeXX-tDfX6Qoxc1uRhFib-d-m_-8DNkf6tA0CkJeojo5Vrew_ORRkV-AivhuRNW1co9taL3w3ff6LxTl9BBNoZ0Pnm34/s1600/mac2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgk7btmMwiHwXZdz6pz17ts_m3hWsS7716eUPX7cxR3G6_9MUNOeXX-tDfX6Qoxc1uRhFib-d-m_-8DNkf6tA0CkJeojo5Vrew_ORRkV-AivhuRNW1co9taL3w3ff6LxTl9BBNoZ0Pnm34/s320/mac2.png" width="224" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">American Commute: <a href="http://eprints.whiterose.ac.uk/89361/7/WRRO_89361.pdf" target="_blank">working paper</a></td></tr>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-26512365880859670752015-08-28T15:47:00.000+01:002015-09-20T21:45:16.512+01:00Mapping the American Commute<div class="separator" style="clear: both; text-align: center;">
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<span style="background-color: white;"><b>Update, 20 September 2015:</b> s</span>croll to the bottom of the post if you want to download the data.<br />
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One of my summer projects this year has been attempting to map the American commute, following earlier work on a similar subject. Put simply, I've attempted to put together a map which shows commuting connections between locations in the contiguous United States, using the most fine-grained data I could find. Some of the results of this went into a recent piece in <a href="http://www.wired.com/2015/08/pretty-maps-bay-area-hellish-commutes/" target="_blank">WIRED</a>, and also <a href="http://www.citymetric.com/transport/how-do-you-map-city-no-centre-commuting-patterns-san-francisco-bay-area-1245" target="_blank">CityMetric</a>, and the larger piece of work it's based on is part of on-going research into the best ways of mapping commuting flows. The main images are below, followed by some more technical information. For now, all you need to know is that these images show commuting connections of 100 miles or less between Census tracts in the lower 48 states. You'll have to forgive me if your city isn't labelled! </div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnGD5wXuPFORiLDEwhjQaZNDpxO6mBBrdAdODIoFZa-5eQokHF1QeGmn_UevkBKcsCxfzSXW1NGZyKI3MKrnAKrnpfAWmmiyfejnxCCseIxbsYv7vUuXuoEd_sqtKdnlAWHHQvr4DmnrQ/s1600/us_lower_48_with_labels_and_text.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhnGD5wXuPFORiLDEwhjQaZNDpxO6mBBrdAdODIoFZa-5eQokHF1QeGmn_UevkBKcsCxfzSXW1NGZyKI3MKrnAKrnpfAWmmiyfejnxCCseIxbsYv7vUuXuoEd_sqtKdnlAWHHQvr4DmnrQ/s320/us_lower_48_with_labels_and_text.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Higher resolution image available <a href="http://ajrae.staff.shef.ac.uk/img/us_lower_48_with_labels_and_text.png" target="_blank">here</a></td></tr>
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And now some zoomed in versions...<br />
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTjL35U-e1j1yw-4m9_9EKaDbFyfgfdWeYfbatIy9lL81CQOxyMWnx2wD1n3g_FwpHlqcgb4qgEBgUtv7sMhK_wHi5igTHGrMcxtqCKqnKKEy-SVD2Z4a1nhdBrQ_Oz1mlySiV8pB2kPc/s1600/west_coast.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTjL35U-e1j1yw-4m9_9EKaDbFyfgfdWeYfbatIy9lL81CQOxyMWnx2wD1n3g_FwpHlqcgb4qgEBgUtv7sMhK_wHi5igTHGrMcxtqCKqnKKEy-SVD2Z4a1nhdBrQ_Oz1mlySiV8pB2kPc/s320/west_coast.png" width="146" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Zoom in of the west coast</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf7Gd8IqbVtyZmmr0o7t8qZOCala5JbCvZWWtzr65r4Jy0o7hlZNLtHeoD33_M8Dfy7Ah8HYB_a-9MItBkM0am-bm-pXb1MzyApLKTHjRqh5PfxF4JpM3nfQxDFF2m-yWaMmpO45gN_vw/s1600/texas_etc.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjf7Gd8IqbVtyZmmr0o7t8qZOCala5JbCvZWWtzr65r4Jy0o7hlZNLtHeoD33_M8Dfy7Ah8HYB_a-9MItBkM0am-bm-pXb1MzyApLKTHjRqh5PfxF4JpM3nfQxDFF2m-yWaMmpO45gN_vw/s320/texas_etc.png" width="255" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Texas, and beyond!</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG_kKO0UaKf_WISPbNOPRA82ThH3L03kxD0T_iEsNKjRhsY9P8SU-aq8gJTA3NFF5OQ_TYpzfDqoDu74_tE1a_4yPfsO8mjWco1Ezfbng-RpskFM5jkK8IU66raly8Dm9myNY5UxILvCY/s1600/mid_north.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="255" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjG_kKO0UaKf_WISPbNOPRA82ThH3L03kxD0T_iEsNKjRhsY9P8SU-aq8gJTA3NFF5OQ_TYpzfDqoDu74_tE1a_4yPfsO8mjWco1Ezfbng-RpskFM5jkK8IU66raly8Dm9myNY5UxILvCY/s320/mid_north.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Interesting patterns of connectivity in the Midwest</td></tr>
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<tr><td style="text-align: center;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBtK_0uJwz7tPbMmusZwjAR6l1wyaKRhnYkNE6mqhcZ0231QkGXEInvVKRt1FW1wdp02gwZDUjQn2c1pN9Ggt9jBp8oBGn5dwv5BF559bJu8omJbxahLudCjitfgaHWyPkJL1R6g0qeG0/s320/se_us.png" style="margin-left: auto; margin-right: auto;" width="310" /></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Look closely for some interesting inter-connections</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyrfSeQFB_dx5kvP8fzeqx1HKCT5RiRYNJ_-4ah3is7sr13NFrugJcC685R9FyDQOi7wXYxfgWIrb99DPhfvxQHXMZyiuO6Uz5Vh72kmxfW6ltZLIFS1tyU-lGxR4Rvd5dIi0hyVcxajY/s1600/boswash.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyrfSeQFB_dx5kvP8fzeqx1HKCT5RiRYNJ_-4ah3is7sr13NFrugJcC685R9FyDQOi7wXYxfgWIrb99DPhfvxQHXMZyiuO6Uz5Vh72kmxfW6ltZLIFS1tyU-lGxR4Rvd5dIi0hyVcxajY/s320/boswash.png" width="251" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The famous BosWash megalopolis</td></tr>
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<b>But this just shows where people live, doesn't it?</b> Yes it does. But it also shows how the places where people live connect with other places from a functional economic point of view, at a fairly fine-grained level. It offers a slightly different view than just looking at the urban fabric alone which, I might add, is interesting in itself. Mapping flows like this is not exactly new, as <a href="http://www.complexcity.info/files/2011/06/harness-1837-flowmap.pdf" target="_blank">this paper</a> from Arthur Robinson (1955) on Henry Drury Harness (1837) demonstrates. Nonetheless, I haven't seen anyone map travel to work at this resolution for the United States, so I thought I'd have a go myself. </div>
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If you spend some time looking at <a href="http://ajrae.staff.shef.ac.uk/img/us_lower_48_with_labels_and_text.png" target="_blank">the big version</a> of the map you can begin to see how places connect and where there are obvious disconnections, even between places that are not that far apart. One thing that you can pick up from the complete dataset (but not this batch of maps) is the <a href="http://www.census.gov/newsroom/releases/pdf/paper_mega_%20commuters_us.pdf" target="_blank">growth of mega-commuting</a>, as explained by Melanie Rapino and Alison Fields of the United States Census Bureau. </div>
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<b>Background information: </b>the data I used is the most recent tract-to-tract <a href="https://www.fhwa.dot.gov/planning/census_issues/ctpp/data_products/2006-2010_tract_flows/" target="_blank">journey to work dataset </a>from the American Community Survey. This dataset covers journeys to work between the c74,000 census tracts in the United States and the complete dataset has around 4million interactions. I mapped this in QGIS, using methods I've <a href="http://www.undertheraedar.com/2014/10/flow-mapping-with-qgis.html" target="_blank">described previously</a> on this blog. The tricky bits were dealing with the messy FIPS codes, dealing with the size of the dataset, and trying to decide what to label. There is quite a bit of error in the dataset (as acknowledged by the ACS people) and each individual flow line has a margin of error value associated with it, from which I also calculated the coefficient of variation. This is explained in a more detailed working paper, which I expect to publish in the coming months.<br />
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<b>Update, 20 September 2015:</b> there has been quite a bit of interest in the underlying dataset I put together to create the maps, so I have decided to make the whole shapefile available here in the hope that others will find it useful and be able to produce some interesting analysis or visuals from it. I'm hoping someone will do a cool interactive web map of it, but it might be quite technically challenging. If you do use it, make sure you read the associated <a href="http://eprints.whiterose.ac.uk/89361/7/WRRO_89361.pdf" target="_blank">working paper</a>, which explains the process and the underlying data. One word of warning: the uncompressed file is pretty big so you'll need a good computer.<br />
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Mapping the American Commute: <a href="https://www.dropbox.com/sh/uqm1bb8xp6txaje/AAA9J5rOjkNocSuQLLEkSSiqa?dl=0" target="_blank">download the data</a> (213MB, zipped shapefile)<br />
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-18446612762720031592015-08-04T21:27:00.000+01:002015-08-04T21:27:15.684+01:00"The Regional World", version 2<div style="text-align: justify;">
I recently came back to <a href="https://cartodb.com/gallery/" target="_blank">CartoDB</a> to do a bit of experimenting for some GIS work I'm doing this autumn, so I decided to revisit a topic I looked at before: sub-national regions of the world. In a previous version I posted via Twitter I took <a href="http://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-1-states-provinces/" target="_blank">sub-national boundaries</a> of the world and put together an interactive map (in about 15 minutes, so it wasn't very good). I've now produced a better one. It's not perfect but I have managed to add in an equal area projection version and other simple features - such as scale-dependent labelling and line styling.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiiQNlzvuILzfN_tw30Y0dEy2dKLWJSxf-i5J8vhKbnI0J5VLfSz-YjIZXP4sZot9uirNNt5bsK0MP_TCRR6GV_PrqQXQYO8iPZ-w3x4mrvxlXrM-zBRdK3LWxcRCZiOWDwSJKo7sykyG4/s1600/regional_world1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="171" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiiQNlzvuILzfN_tw30Y0dEy2dKLWJSxf-i5J8vhKbnI0J5VLfSz-YjIZXP4sZot9uirNNt5bsK0MP_TCRR6GV_PrqQXQYO8iPZ-w3x4mrvxlXrM-zBRdK3LWxcRCZiOWDwSJKo7sykyG4/s320/regional_world1.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="https://alasdair.cartodb.com/viz/44f0123c-39de-11e5-8e83-0e018d66dc29/embed_map" target="_blank">The Regional World - version 2</a></td></tr>
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<a href="https://en.wikipedia.org/wiki/List_of_country_subdivisions_by_area" target="_blank">According to Wikipedia</a>, the largest sub-national divisions in the world are the Sakha Republic (Yakutiya) in Russia, Western Australia, and Krasnoyarsk Krai, also in Russia. The first two are more than ten times the size of the UK (which is 244,000 sq km) and number three almost is. If you click on the link above to go to the map then you'll see that you can also click on the <a href="https://alasdair.cartodb.com/viz/92d007c6-3a99-11e5-8097-0e49835281d6/embed_map" target="_blank">equal area version</a>. I did this because web maps often default to the Mercator projection, which causes massive distortion towards the poles and leads people into thinking Greenland is bigger than Africa, which of course <a href="http://www.pratham.name/mercator-projection-africa-vs-greenland.html" target="_blank">it isn't</a>.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiVUxJJx1Vmcl-0Ke1NNQirFxaUyQ8we_Wz560FiY6wg7JKQD4T11EVxcyOWlgZ1fz2sGUIT2VoXpnMCr57dBhUK6D5E2a2FZTWRG9cQhpxp7L11Hwd0kT44VmZPiCRJz9H_wNF80dNApg/s1600/regional_world2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="172" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiVUxJJx1Vmcl-0Ke1NNQirFxaUyQ8we_Wz560FiY6wg7JKQD4T11EVxcyOWlgZ1fz2sGUIT2VoXpnMCr57dBhUK6D5E2a2FZTWRG9cQhpxp7L11Hwd0kT44VmZPiCRJz9H_wNF80dNApg/s320/regional_world2.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The Regional World - <a href="https://alasdair.cartodb.com/viz/92d007c6-3a99-11e5-8097-0e49835281d6/embed_map" target="_blank">equal area projection</a></td></tr>
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The equal area projection does of course mean that areas towards the poles are extremely distorted, but that's part of the deal with some map projections. I've taken the administrative boundaries at face value, but of course they may not be 100% accurate, as the authors of the data acknowledge:</div>
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<span style="font-size: large;">"This is the toughest dataset to keep current. Unlike the United States, other countries constantly rearrange their admin-1 units, slicing and combining them on a regular basis."</span></div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgb4qgjHblP08TEyFL-hzq5gd1Jt8i25YBtbwFunGQvE652YQMmzKfSken_HVEFXHEuKZKnNG6964K__D0UHvbVh8VhbFYOme0E5NUOkLrkzU8YsG0cNE9HXPdaT2mUTx6ZWDuvg9kvWo/s1600/regions_disclaimer.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="156" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgb4qgjHblP08TEyFL-hzq5gd1Jt8i25YBtbwFunGQvE652YQMmzKfSken_HVEFXHEuKZKnNG6964K__D0UHvbVh8VhbFYOme0E5NUOkLrkzU8YsG0cNE9HXPdaT2mUTx6ZWDuvg9kvWo/s320/regions_disclaimer.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="http://www.naturalearthdata.com/downloads/10m-cultural-vectors/10m-admin-1-states-provinces/" target="_blank">Read more about the data</a></td></tr>
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You'll notice that I have put links to a small number of countries on the main map. I chose these because I find them interesting, that's all. This was part experiment with CartoDB and a little SQL (projection) and CSS (scale-dependent styling), part GIS project, part teaching material, partly driven by my interest in <a href="http://www.tandfonline.com/action/journalInformation?show=editorialBoard&journalCode=rsrs20#.VcDffvlVhBc" target="_blank">regions</a> more generally, and part pre-holiday wind-down. In relation to the latter, just for fun, I have hidden two little artefacts in the main map that only appear when you zoom to a certain level at two places on earth. </div>
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<b>Can you find them? </b></div>
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<span style="font-size: x-small;">Answers via <a href="https://twitter.com/undertheraedar" target="_blank">Twitter</a> or e-mail...</span></div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-86933529610795948922015-07-20T22:39:00.000+01:002015-07-20T22:41:29.953+01:00Urban footprints: some building outline data sources<div style="text-align: justify;">
This is an informational post about where to find building outline data, which I've used a lot in previous GIS projects. It might also be of interest to architects, engineers and anyone interested in urban studies and planning more generally. I like using this kind of data to explore cities as it gives us a good idea of the layout of the urban fabric, as in the example below (New Orleans). The links mainly refer to data from the US, Canada and Great Britain but other parts of the world are covered to various extents by OpenStreetMap.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVvStQ9bYh3WqiNGjgz870Cfq4uiGkFEre1LjAtdKOp2jv3xWuiwBKSMEpK-kDUIOgPPYS9Z6aIQ-B1pLVdpw7pYmYV7fD22VsHShq-VI5TYpKEcpFIZxdTubQujVwOJqbsqKoGhpvj3A/s1600/nola.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjVvStQ9bYh3WqiNGjgz870Cfq4uiGkFEre1LjAtdKOp2jv3xWuiwBKSMEpK-kDUIOgPPYS9Z6aIQ-B1pLVdpw7pYmYV7fD22VsHShq-VI5TYpKEcpFIZxdTubQujVwOJqbsqKoGhpvj3A/s320/nola.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">New Orleans</td></tr>
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Let's start big, with OSM... Steve Bernard has produced <a href="https://www.youtube.com/watch?v=Zsf4OxUDS44" target="_blank">an excellent video</a> which explains how you can get OpenStreetMap data directly into QGIS very simply - he uses Madrid in the example. The accuracy and coverage varies a great deal across the world, so you need to bear this in mind when downloading and using it - but on the whole it is a fantastic resource. The example below shows Mogadishu, where the coverage is incomplete for buildings but pretty good for the road network. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe_MBb9baoaD-3rgZGSp_4DylJ4ws0yMkbxlYrz5DMT94lJsematK6KWLqTMhOGncsN7TUTJlibMjxGk90OeBMEo6_2zNv4j2L-sAoRXI7EU9i-z4qH0UiPq4jpi-VDE5fA9ByYivp6E4/s1600/mogadishu.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="215" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe_MBb9baoaD-3rgZGSp_4DylJ4ws0yMkbxlYrz5DMT94lJsematK6KWLqTMhOGncsN7TUTJlibMjxGk90OeBMEo6_2zNv4j2L-sAoRXI7EU9i-z4qH0UiPq4jpi-VDE5fA9ByYivp6E4/s320/mogadishu.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">© OpenStreetMap contributors</td></tr>
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Another useful OSM-related resource with decent global city coverage is <a href="https://cadmapper.com/" target="_blank">CAD Mapper</a>, where you can download areas up to 1km square for free. However, I'm focusing on open data today so will not go into detail on this. The best OSM download source is I think <a href="http://download.geofabrik.de/" target="_blank">GEOFABRIK</a> (German for 'geo factory), a German GIS consultancy who extract and process OSM data and then make it available for free online. It's really nicely structured and easy to find what you're looking for. Here's the download page for New Zealand, for example - followed by the contents, where you can see the building data on top of a current OSM base map. At time of writing, the zipped shp folder for the whole of New Zealand was 146MB.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBZ32gL2D0pw-mCHA-_7R2pdOzTwOg9NqJbGEvsqj1QEBSMv_OCBBhGdOxeuSE0uMlT-GtVxL7qUTUSWJukQhxz7ygnCmhG2Xa-GOt_-Q0XOc48pTXyMCTuVpENugvW9n5NVjnAeOwueA/s1600/nz.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="241" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgBZ32gL2D0pw-mCHA-_7R2pdOzTwOg9NqJbGEvsqj1QEBSMv_OCBBhGdOxeuSE0uMlT-GtVxL7qUTUSWJukQhxz7ygnCmhG2Xa-GOt_-Q0XOc48pTXyMCTuVpENugvW9n5NVjnAeOwueA/s320/nz.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The New Zealand GEOFABRIK download page (20 July 2015)</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRj7MoFg2jgUepK4Mb0qmxit9jp_fJ3vjVlHaDreM7h05v-DBMpG_ZQTKCvHLocUOm-db630CcARK0X1PtzvbsrZd8_xw6lCV7-kGrguSEYHob3Kb4SjJKGxKc9v-jp43LCPy4aeP64hM/s1600/auck_OSM.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="215" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgRj7MoFg2jgUepK4Mb0qmxit9jp_fJ3vjVlHaDreM7h05v-DBMpG_ZQTKCvHLocUOm-db630CcARK0X1PtzvbsrZd8_xw6lCV7-kGrguSEYHob3Kb4SjJKGxKc9v-jp43LCPy4aeP64hM/s320/auck_OSM.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Auckland, NZ - very good building coverage here</td></tr>
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The OSM sources are great, since the <a href="https://www.openstreetmap.org/copyright" target="_blank">licence</a> is very generous and you can use the data for just about anything, so long as it's properly cited. However, many towns, cities and counties across the world also provide building footprint or outline data (the terminology varies from place to place) so I've put together a list below of ones I know about. Some of them (e.g. Detroit, NYC) cover land parcels or tax lots so are slightly different but in the main it's just building outlines. I've included visuals for some of the datasets, so you can get an idea of what they look like.</div>
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<a href="http://www.nyc.gov/html/dcp/html/bytes/applbyte.shtml" target="_blank">New York City</a> - from the BYTES of the BIG APPLE website you can download the MapPLUTO dataset, for all 5 Boroughs in New York City. Tax lot level rather than building outlines, but it's an extremely rich dataset with loads of useful land use planning variables in it, including 'year built' and number of floors. A little sample of the data are shown below, for the area around Central Park.</div>
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<tr><td class="tr-caption" style="text-align: center;">A little sample of the data (using Qgis2threejs)</td></tr>
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<a href="http://www.cityofchicago.org/city/en/depts/doit/supp_info/gis_data.html" target="_blank">Chicago</a> - the building footprints layer is avaiable in two versions online, one of which says it is deprecated but I've heard from the Chicago GIS team that this isn't the case. It's just that due to limited staff the dataset is only edited when necessary. Also contains a 'year built' and height variable.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyuodebAAStueS7hLThYQbP7gmg-3zkTgFPhVaLNwhBUmQBhBX6b6bhjJA1JBg2DxrwIDwtu8GQ_mcnILreAu0Jv_dB9_BFP11pKCRgEpRtHIImntWgXVAQWfk5MjthXT-P7Voahp_EHo/s1600/chicago_3d_buildings-1.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="236" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgyuodebAAStueS7hLThYQbP7gmg-3zkTgFPhVaLNwhBUmQBhBX6b6bhjJA1JBg2DxrwIDwtu8GQ_mcnILreAu0Jv_dB9_BFP11pKCRgEpRtHIImntWgXVAQWfk5MjthXT-P7Voahp_EHo/s320/chicago_3d_buildings-1.png" width="320" /></a></div>
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<a href="https://data.sfgov.org/Geographic-Locations-and-Boundaries/Building-Footprints-Zipped-Shapefile-Format-/jezr-5bxm" target="_blank">San Francisco</a> - another really good city buildings dataset, from SF OpenData. Also lots of useful variables in this dataset, including height. I really like this one.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjtmHQj92j20tXaai-o5q_KNfQRHanzmpIsKK777jcN04U7mdeEzQPiLml4Re7MLASdCmrqpftv1Sj5tbHPBvdkqThIk3BGNZB_-OjHzYL1Tp_86LkzT2onxcjonRMb-0FHDfFdNmx_lPI/s1600/sf_3d.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="211" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjtmHQj92j20tXaai-o5q_KNfQRHanzmpIsKK777jcN04U7mdeEzQPiLml4Re7MLASdCmrqpftv1Sj5tbHPBvdkqThIk3BGNZB_-OjHzYL1Tp_86LkzT2onxcjonRMb-0FHDfFdNmx_lPI/s320/sf_3d.png" width="320" /></a></div>
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<a href="http://gis.dallascityhall.com/EnterpriseGIS/shapezip.htm" target="_blank">Dallas</a> - you'll probably get a disclaimer box in a pop-up when you go to download this. I've linked to the general GIS page and the file you want is called Structures (Building Footprints) in the Planimetric Data section - it's about 81MB to download and the unzipped file is well over 100MB.</div>
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<a href="http://gis.atlantaga.gov/apps/gislayers/download/" target="_blank">Atlanta</a> - again, I've linked to the GIS page, this time from the City of Atlanta and you need to download the 'Impervious Buildings' layer. If you're looking to map the sprawl of Atlanta, this won't work as it covers the City area only. Still, a very useful dataset.</div>
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<a href="http://data.denvergov.org/dataset/city-and-county-of-denver-building-outlines" target="_blank">Denver </a>- excellent open data from Denver. This dataset covers all permanent structures and buildings for a 152 square mile area of the City and County of Denver. Available in a number of different formats.</div>
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<a href="https://data.seattle.gov/dataset/2009-Building-Outlines/y7u8-vad7" target="_blank">Seattle</a> - this dataset was created in 2009 by Pictometry International Corp but is now in the public domain. It is available via the City of Seattle's data website.</div>
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<a href="http://egis3.lacounty.gov/dataportal/2011/04/28/countywide-building-outlines/" target="_blank">Los Angeles</a> - this is a fantastic dataset for the County (not just the City) of Los Angeles, which is the most populous county in the United States (just over 10 million). Made available via the LA County GIS Data Portal. It is a little hefty (581MB) so be careful! In the example below I show all the buildings in LA County but the City of Los Angeles in dark shading, just to emphasise its crazy shape.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBbegzC8l4UmmT5Lh9E_Yv2R_Lwh9gKYLp6GG45MkybGeqsyn6XDYfL2TOooNTVJOIdXEWDSeokbbiUH_ixU8e11xDDcYfFzkNgOCx7yJeaPf-f4qvl73L39lDU4z3Cg24hv8giqAC8BM/s1600/la_city_vs_county1000.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjBbegzC8l4UmmT5Lh9E_Yv2R_Lwh9gKYLp6GG45MkybGeqsyn6XDYfL2TOooNTVJOIdXEWDSeokbbiUH_ixU8e11xDDcYfFzkNgOCx7yJeaPf-f4qvl73L39lDU4z3Cg24hv8giqAC8BM/s320/la_city_vs_county1000.png" width="288" /></a></div>
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<a href="http://boston.maps.arcgis.com/home/item.html?id=c423eda7a64b49c98a9ebdf5a6b7e135" target="_blank">Boston</a> - this was created in 2012 and is available via the City of Boston. Contains a number of different fields, including base elevation of the structures, the elevation of the highest point above sea level and fields on building type.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgdqVjdHSxCScvw36On2IZ9zrM49uPFofik226ZN5AH4WojkWcbzDYuupKx0TM66R_V_LyNpEJ9Udvm0WkYgNCPom3VCRW74R-p4ApBFVCIBDtJGw-Syd6hLbUqiUtqXG1ND4nQIQuTaVM/s1600/bos.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgdqVjdHSxCScvw36On2IZ9zrM49uPFofik226ZN5AH4WojkWcbzDYuupKx0TM66R_V_LyNpEJ9Udvm0WkYgNCPom3VCRW74R-p4ApBFVCIBDtJGw-Syd6hLbUqiUtqXG1ND4nQIQuTaVM/s320/bos.png" width="320" /></a></div>
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<a href="http://d3.d3.opendata.arcgis.com/datasets/7cfed5afb7654e2495ef4c1ead320aa5_0" target="_blank">Detroit</a> - like New York, not strictly a buildings outline file but instead a property lot level dataset. Very impressive dataset produced by Data Driven Detroit's Motor City Mapping project. I've used this data a lot in talks and teaching as it's a really good example of its type.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiqsHXqrYidD_-NQv5y3f7RK9uKZoaLnBN9wREucsKjZn-Bcl2OwFw7-FqRVFSx4Sp8574Si4VgUBz2aTL_vfBzh76Xw6-yAcAl_Oidh85jScLpjYV0W5Vj02uK-O5ejde-Q2vEXQ4QdnM/s1600/detroit_crop.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="201" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiqsHXqrYidD_-NQv5y3f7RK9uKZoaLnBN9wREucsKjZn-Bcl2OwFw7-FqRVFSx4Sp8574Si4VgUBz2aTL_vfBzh76Xw6-yAcAl_Oidh85jScLpjYV0W5Vj02uK-O5ejde-Q2vEXQ4QdnM/s320/detroit_crop.png" width="320" /></a></div>
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Now some links to further datasets which I know of but haven't used that much...</div>
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<a href="http://dcatlas.dcgis.dc.gov/metadata/BldgPly_3D.html" target="_blank">Washington DC</a> - link is to the download page, but direct link to zip is <a href="http://dcatlas.dcgis.dc.gov/download/BldgPly_3D.zip" target="_blank">here</a> (559MB unzipped)</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3X5eXsprI1AxGW_oATQ9nejmYTwFGsh9QknAXQ-rErpUn-Dju2Ut-q40Sc3o2vHwNZNMtnI2pnEY3h33-dyY4JqwZe37MDMyaMZTIz6dYY5ReRgBrQZxmAD5oF4hdhpaRqp5Y0oeHQZs/s1600/dc.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="215" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg3X5eXsprI1AxGW_oATQ9nejmYTwFGsh9QknAXQ-rErpUn-Dju2Ut-q40Sc3o2vHwNZNMtnI2pnEY3h33-dyY4JqwZe37MDMyaMZTIz6dYY5ReRgBrQZxmAD5oF4hdhpaRqp5Y0oeHQZs/s320/dc.png" width="320" /></a></div>
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<a href="https://data.baltimorecity.gov/browse?category=Geographic" target="_blank">Baltimore</a> - the top link on this page</div>
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<a href="https://www.opendataphilly.org/dataset/buildings/resource/2abe6e0e-3d82-4551-a06b-8c2dfd17592c" target="_blank">Philadelphia</a> - via OpenDataPhilly</div>
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<a href="http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographic-information-massgis/datalayers/ftpstructures.html" target="_blank">Massachusetts</a> - buildings for a wide range of towns and cities in the state</div>
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<a href="http://www.bouldercounty.org/gov/data/pages/gisdldata.aspx" target="_blank">Boulder</a> - this is from Boulder County, Colorado. Available in a number of different file formats.</div>
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<a href="https://bloomington.in.gov/documents/viewDocument.php?document_id=2455;dir=building/buildingfootprints/shape" target="_blank">Bloomington, Indiana</a> - one of many smaller cities with excellent geodata</div>
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<a href="https://data.nola.gov/Geographic-Base-Layers/Building-Footprint/qb9t-4p8r" target="_blank">New Orleans</a> - an excellent dataset, not just because of the unusual shape of the city!</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcVYtcZyIwBl_wqaY5e5x41_ng7c3a7tUaHU2GhrnKmVdSgptUUjcDTgwS_Mqe772kPkbQMiiN8DQmfSLvDxIne9KTyMx5h0hROeqCOw7uILp4MsjS5GT5oqeHRlOJV2q8RI1jFlQyHJ8/s1600/nola.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="287" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhcVYtcZyIwBl_wqaY5e5x41_ng7c3a7tUaHU2GhrnKmVdSgptUUjcDTgwS_Mqe772kPkbQMiiN8DQmfSLvDxIne9KTyMx5h0hROeqCOw7uILp4MsjS5GT5oqeHRlOJV2q8RI1jFlQyHJ8/s320/nola.png" width="320" /></a></div>
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<a href="http://www1.toronto.ca/wps/portal/contentonly?vgnextoid=d431d477f9a3a410VgnVCM10000071d60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD" target="_blank">Toronto</a> - don't be confused by the '3D Massing' terminology here. Scroll down to the 'Data download' section</div>
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<a href="http://data.vancouver.ca/datacatalogue/buildingFootprint1999.htm" target="_blank">Vancouver</a> - doesn't cover the whole city and they were digitised in 1999 but still a useful dataset.</div>
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<a href="http://www.regionofwaterloo.ca/en/regionalGovernment/BuildingFootprints.asp" target="_blank">Waterloo</a> - this is from the Region of Waterloo and was up to date as of January 2014.</div>
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<a href="http://data.gov.au/dataset/36f1ca48-ed2d-4a58-a15b-6fb4b97fdbd7/resource/00c75c25-2cd2-41ea-98bf-bae44bcca8ec" target="_blank">Hobart</a>, Tasmania - an nice example of building data from Hobart in Australia. Contains a 'year constructed' variable.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjnjNr6oKv1bx3GMA371xSH0vPJuMP0x-CGVqsr68TtNuM6a-oBvF_JnE0xVPXiqCDtTJFyyKrD457g0iy8N7Rdy8Y5GZSBuljmaVf7ZalAxNrGezQpjpLOgogXTtBEZNTDfCca-S6_FoQ/s1600/hobart.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="215" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjnjNr6oKv1bx3GMA371xSH0vPJuMP0x-CGVqsr68TtNuM6a-oBvF_JnE0xVPXiqCDtTJFyyKrD457g0iy8N7Rdy8Y5GZSBuljmaVf7ZalAxNrGezQpjpLOgogXTtBEZNTDfCca-S6_FoQ/s320/hobart.png" width="320" /></a></div>
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<a href="https://koordinates.com/layer/1474-wellington-city-building-footprints/" target="_blank">Wellington, NZ</a> - can't <a href="http://worldmapswithout.nz/" target="_blank">overlook</a> New Zealand! I think you need to register to download this but it's Creative Commons 3 so still open. </div>
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The list wouldn't be complete without mentioning <a href="https://www.ordnancesurvey.co.uk/opendatadownload/products.html" target="_blank">OS OpenData</a> for Great Britain, provided by Ordnance Survey. A new dataset with detailed buildings became available in March (the OS Open Map - Local) dataset. The building data is a very small part of this collection but one I find very interesting. I've patched together a few cities <a href="http://ajrae.staff.shef.ac.uk/buildings/" target="_blank">here</a> to get the ball rolling but you can download your own. There's also a 'tile finder' to help you identify which OS tile you need to cover your area of interest. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQJOVhCXdx39nf9sCxr5f4J6ax8OHIQIvn0yo0AeoElOdkdyyN9ZG3ear5FfPOjMDyxWUxCogJLVEmeLaaNgX5teKKWQnKm6BMMyQQOIctuyRUQCCC2mymeZwNibNR6XcNP4pkv2lXL78/s1600/os_buildings.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="267" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgQJOVhCXdx39nf9sCxr5f4J6ax8OHIQIvn0yo0AeoElOdkdyyN9ZG3ear5FfPOjMDyxWUxCogJLVEmeLaaNgX5teKKWQnKm6BMMyQQOIctuyRUQCCC2mymeZwNibNR6XcNP4pkv2lXL78/s320/os_buildings.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">This could <a href="http://ajrae.staff.shef.ac.uk/buildings/" target="_blank">save you some time</a> </td></tr>
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I think this just about covers it. Get in touch if you have any other great data sources for building outlines.</div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-25274751741578577632015-07-12T21:59:00.000+01:002015-07-14T17:14:08.042+01:00Mapping the Polycentric Metropolis: journeys to work in the Bay Area<div style="text-align: justify;">
I’ve recently been writing and thinking about polycentric urban regions, partly because I’m interested in how places connect (or not) for one of my research projects, and partly because I’ve been experimenting with ways to map the connections between places in polycentric urban regions. There was quite a lot of the latter in Peter Hall and Kathy Pain’s ‘<a href="https://books.google.co.uk/books/about/The_Polycentric_Metropolis.html?id=UYb6Kfgo8O8C&source=kp_cover&hl=en" target="_blank">The Polycentric Metropolis</a>’ from 2006 but given that the technology has moved on a little since then I thought I’d explore the topic in more detail. Mind you, I’ve also been looking back on Volumes 1 to 3 of the <a href="https://archive.org/details/chicagoareatrans01chic" target="_blank">Chicago Area Transportation Study</a> of 1959 as a reminder that technology hasn’t moved on as much as we think – their ‘Cartographatron’ was capable of mapping over 10 million commuting flows even then (though it was the size of a small house and required a team of technicians to operate it – see bottom of post for a photo).<br />
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYKBkC3LL2P_C87fGCCaXbW2kycdHhbVkK6wIJsvAaRQAbpW0okLapfnI2Z3GQ-jaRnv6VJn-hCntJntZL8ZsOY8ftuHjmZI4vLa5bWwwtzJ39Qnd1CIz3JXQ4GuGC8baooeWtvwcs0bI/s1600/sf_mini.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="278" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgYKBkC3LL2P_C87fGCCaXbW2kycdHhbVkK6wIJsvAaRQAbpW0okLapfnI2Z3GQ-jaRnv6VJn-hCntJntZL8ZsOY8ftuHjmZI4vLa5bWwwtzJ39Qnd1CIz3JXQ4GuGC8baooeWtvwcs0bI/s320/sf_mini.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Are you part of the big blue blob?</td></tr>
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Anyway, to the point… What’s the best way of mapping polycentricity in an urban region? For this, I decided to look at the San Francisco Bay Area since it has been the subject of a few studies by one of my favourite scholars, <a href="http://ced.berkeley.edu/ced/faculty-staff/robert-cervero" target="_blank">Prof Robert Cervero</a> of UC Berkeley. Also, <a href="http://www.census.gov/newsroom/releases/pdf/paper_mega_%20commuters_us.pdf" target="_blank">a paper</a> by Melanie Rapino and Alison Fields of the US Census Bureau identified the Bay Area as the region with the highest percentage of ‘mega commuting’ in the United States (traveling 90 or more minutes and 50 or more miles to work). Therefore, I decided to look at commuting flows between census tracts in the 9 counties of the Bay Area, from Sonoma County in the north to Santa Clara County in the south. I’ve used a cut-off of 30 miles here instead of the more generous 50 mile cut-off used by Rapino and Fields. I also mapped the whole of the United States in this way, but that’s for another day.</div>
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The series of maps below illustrate both patterns of commuting in the Bay Area and the different approaches I’ve taken in an attempt to capture the essence of polycentrism in the area. I don’t attempt to capture the misery of some of these commutes, since for that I’d need a different kind of technology. But, I do think the animations in particular capture the polycentric nature of commuter flows. If you’re represented by one of the dots in the images below, thanks a lot for taking part!</div>
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Let’s start with a simple representation of commutes of over 30 miles from San Francisco County (which is coterminous with the City of San Francisco). The animated gif is shown below and you can click the links to view the sharper video file (mp4) in your browser (so long as you're on a modern browser). The most noticeable thing here is the big blue blob© making its way down from San Francisco to Palo Alto, Mountain View and Cupertino in Santa Clara County. In total, the blue dots represent just over 15,000 commuters going to 803 different destination census tracts. I’m going to take a wild guess and suggest that some of these commutes are by people who work at Stanford, Google and Apple. But it probably also includes people working at NASA Ames Research Center, Santa Clara University and locations in San Jose. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgib32ykspLBCQRj_vKXN_RjIHxsHS6sJ9eZsy8NCO1u-g3UMj_g2vOSRdSgduw1qzCgqY55thAyJ9zW5YYvE-bmj05bbAD7dSunYP5wKf81HTpGT5lrvcwi9_EVrC7Ug774iVTLBoFO7U/s1600/sf_out_120715v2.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="273" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgib32ykspLBCQRj_vKXN_RjIHxsHS6sJ9eZsy8NCO1u-g3UMj_g2vOSRdSgduw1qzCgqY55thAyJ9zW5YYvE-bmj05bbAD7dSunYP5wKf81HTpGT5lrvcwi9_EVrC7Ug774iVTLBoFO7U/s320/sf_out_120715v2.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">View <a href="http://ajrae.staff.shef.ac.uk/bayarea/sf_out_120715.mp4" target="_blank">video file</a> in browser - or click image to enlarge gif</td></tr>
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These patterns aren’t particularly surprising, since there has been a lot of press coverage about San Francisco’s <a href="http://articles.latimes.com/2014/jan/24/opinion/la-ed-google-bus-san-francisco-20140123" target="_blank">bus wars</a> and commutes of this kind. However, there is a fairly significant dispersal of San Francisco commuters north and east, even if the numbers don’t match those of the big blue blob. By the way, from San Francisco it's about 33 miles to Palo Alto, 39 miles to Mountain View, 42 to Cupertino and 48 to San Jose. </div>
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The first example above doesn’t reveal anything like the whole story, though. There are actually quite a lot of commuters who travel in the opposite direction from Santa Clara County to San Francisco but more widely the commuting patterns in the Bay Area – a metro area of around 7.5 million people – resembles a nexus of mega-commuting. This is what I’ve attempted to show below, for all tract-to-tract connections of 10 people or more, and no distance cut-off. The point is not to attempt to display all individual lines, though you can see some. I’m attempting to convey the general nature of connectivity (with the lines) and the intensity of commuting in some areas (the orange and yellow glowing areas). Even when you look at tract-to-tract connections of 50 or more, the nexus looks similar.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiqO07nBYbOETXCwi1ru8A8AE2w2oxiZw1gXZlQKs5L8T8xUwNO2f1NFwm-5ygEbkNdnh47em_taYHpkYtJRNuF7d5pK5ZLTiD1_21DC9jLXWUKFv1pdyVIkIMyoTPRHXkuX1-X1xwCoPs/s1600/bay_area_commuting_flow_lines-v2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="273" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiqO07nBYbOETXCwi1ru8A8AE2w2oxiZw1gXZlQKs5L8T8xUwNO2f1NFwm-5ygEbkNdnh47em_taYHpkYtJRNuF7d5pK5ZLTiD1_21DC9jLXWUKFv1pdyVIkIMyoTPRHXkuX1-X1xwCoPs/s320/bay_area_commuting_flow_lines-v2.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Click image to view larger version</td></tr>
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<tr><td class="tr-caption" style="text-align: center;">Stronger connections - click image to view larger version</td></tr>
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If we zoom in on a particular location, using a kind of ‘spider diagram’ of commuting interactions, we can see the relationships between one commuter destination and its range of origins. In the example below I’ve taken the census tract where the Googleplex is located and looked at all Bay Area Commutes which terminate there, regardless of distance. In the language of the seminal Chicago Area Transportation Study I mentioned above, these are ‘desire lines’ since this represents ‘the shortest line between origin and destination, and expresses the way a person would like to go, if such a way were available’ (CATS, 1959, p. 39) instead of, for example, sitting in traffic on US Route 101 for 90 minutes. According to the data, this example includes just over 23,000 commuters from 585 different locations across the Bay Area. I've also done an animated line version and a point version, just for comparison.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjGKLKD30sjDl9Pe6_MkpeDubzN7kQRrXtg9zXNsB8tVnEsQfyg0vm0qHXHXwnrgmfM8wSqZGRjgIwz-J7i0zhwGnqYwfh2tHilQ2uFgXPnsr3G4rEwIxDWdz9QxkDS3fxS0t3LHtVs3_o/s1600/mountain_view_all.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="273" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjGKLKD30sjDl9Pe6_MkpeDubzN7kQRrXtg9zXNsB8tVnEsQfyg0vm0qHXHXwnrgmfM8wSqZGRjgIwz-J7i0zhwGnqYwfh2tHilQ2uFgXPnsr3G4rEwIxDWdz9QxkDS3fxS0t3LHtVs3_o/s320/mountain_view_all.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Commuting connections for the Googleplex census tract</td></tr>
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<tr><td class="tr-caption" style="text-align: center;">Animated spider diagram of flows to Mountain View</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEij4uy3Vr2Xb9XO0Kl6kCWBg2RFd7EQvvzKc_fYvT3YOgSO93QOM7BgfL7tI4xJ4Nf4XuvLWZIBluTXGWRhBgQLQPT7Zr6H30rypsHkJCbdfCUIS6ZkDmNwhfr-PQNty_fFkbyv-qaexWg/s1600/mountain-view.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="273" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEij4uy3Vr2Xb9XO0Kl6kCWBg2RFd7EQvvzKc_fYvT3YOgSO93QOM7BgfL7tI4xJ4Nf4XuvLWZIBluTXGWRhBgQLQPT7Zr6H30rypsHkJCbdfCUIS6ZkDmNwhfr-PQNty_fFkbyv-qaexWg/s320/mountain-view.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Just some Googlers going to work (probably) <a href="http://ajrae.staff.shef.ac.uk/bayarea/to_google_120715.mp4" target="_blank">mp4</a></td></tr>
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Looking further afield now, to different parts of the Bay Area, I also produced animated dot maps of commutes of 30 miles or more for the other three most populous counties – Alameda, Contra Costa and Santa Clara. I think these examples do a good job of demonstrating the polycentric nature of commuting in this area since the points disperse far and wide to multiple centres. Note that I decided to make the dots return to their point of origin – after a slight delay – in order to highlight the fact that commuting is a two way process. The Alameda County animation represents over 12,000 commuters, going to 751 destinations, Contra Costa 25,000 and 1,351, and Santa Clara nearly 28,000 commuters and 1,561 destinations. The totals for within the Bay Area are about 3.3 million and 110,000 origin-destination links.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhVjxp-sFPv-HAMC3EkXUvvY_8D6ntKFma5jT_i5NOLSRaqBdedLRQbO8fyrKOXEAkrSWDLghmSvb6XjTYIWgCn67Z5_YVs2IGs4RTYrkR_ZUWxPws3gDrnlWFkEfraN6eSrCPZ2T9E9Rg/s1600/alameda_out.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="275" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhVjxp-sFPv-HAMC3EkXUvvY_8D6ntKFma5jT_i5NOLSRaqBdedLRQbO8fyrKOXEAkrSWDLghmSvb6XjTYIWgCn67Z5_YVs2IGs4RTYrkR_ZUWxPws3gDrnlWFkEfraN6eSrCPZ2T9E9Rg/s320/alameda_out.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Alameda County commutes of 30+ miles <a href="http://ajrae.staff.shef.ac.uk/bayarea/alameda.mp4" target="_blank">mp4</a></td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgUKIr-zrFayn3-zoV6Q3yMsUHsHIbY0iKM7uZyDv6f1GDO0XBhoEtnD5lXD3Ahtb9_kcVZrraf0BfVogPBbgtsjhWkzpdyQDbEgRoWcdsml2heEzNxo1SFFxc7DOLYtNDEKOjP-h6n28/s1600/contra_costa.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="275" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhgUKIr-zrFayn3-zoV6Q3yMsUHsHIbY0iKM7uZyDv6f1GDO0XBhoEtnD5lXD3Ahtb9_kcVZrraf0BfVogPBbgtsjhWkzpdyQDbEgRoWcdsml2heEzNxo1SFFxc7DOLYtNDEKOjP-h6n28/s320/contra_costa.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Contra Costa County commutes of 30+ miles <a href="http://ajrae.staff.shef.ac.uk/bayarea/contra_costa.mp4" target="_blank">mp4</a></td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhR9FMgo4jg8kaEf-jPFkvDWd4CbQ2QQOQQbh5Oh_y57EauLtkTpCM5BWJ-OX0CnuTvk2dzfPAk_e-PsqhE3YlUXLlWt9mJAiv5YvAnICC5omGIOrVKFvJs8PoXX415x9GxZFAzsyTESIY/s1600/santa_clara.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="275" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhR9FMgo4jg8kaEf-jPFkvDWd4CbQ2QQOQQbh5Oh_y57EauLtkTpCM5BWJ-OX0CnuTvk2dzfPAk_e-PsqhE3YlUXLlWt9mJAiv5YvAnICC5omGIOrVKFvJs8PoXX415x9GxZFAzsyTESIY/s320/santa_clara.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Santa Clara County commutes of 30+ miles <a href="http://ajrae.staff.shef.ac.uk/bayarea/santa_clara.mp4" target="_blank">mp4</a></td></tr>
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Finally, I’ve attempted something which is a bit much for one map, but here it is anyway; an animated dot map of all tract-to-tract flows of 30 or more miles in the Bay Area, with dots coloured by the county of origin. Although this gets pretty crazy half way through I think the mixing of the colours does actually tell its own story of polycentric urbanism. For this final animation I’ve added a little audio into the video file as well, just for fun.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-DN8xXX6jl24dMWkv7bshTNs038EMlXgHgxAxDXm8G7kGHaTo2LsgSNCu81KH_yxNUE3WMkinUbyVSfTM3hrBMsRsLM1h5AGuBapIsv7T2d-c18y6mfJl0_D3RN-gcMvRmZffFE5Deq0/s1600/frame000011.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="275" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-DN8xXX6jl24dMWkv7bshTNs038EMlXgHgxAxDXm8G7kGHaTo2LsgSNCu81KH_yxNUE3WMkinUbyVSfTM3hrBMsRsLM1h5AGuBapIsv7T2d-c18y6mfJl0_D3RN-gcMvRmZffFE5Deq0/s320/frame000011.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A still from the final animation - <a href="http://ajrae.staff.shef.ac.uk/bayarea/bay9.mp4" target="_blank">view here</a></td></tr>
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What am I trying to convey with the final animation? Like I said, it's too much for a single map animation but it's kind of a metaphor for the messy chaos of Bay Area commuting (yes, let's go with that). You can make more sense of it if you watch it over a few times and use the controls to pause it. It starts well and ends well, but the bits in the middle are pretty ugly - just like the Bay Area commute, like I said.</div>
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My attempts to understand the functional nature of polycentric urbanism continue, and I attempt to borrow from pioneers like Waldo Tobler and the authors of the Chicago Area Transportation Study. This is just a little map-based experimentation in an attempt to bring the polycentric metropolis to life, for a region plagued by gruesome commutes. It’s little wonder, therefore, that a recent poll suggested Bay Area commuters were in favour of improving public transit. If you're interested in understanding more about the Bay Area's housing and transit problems, I suggest watching this <a href="https://www.youtube.com/watch?v=OSEkM4okFu8" target="_blank">Google Talk</a> from Egon Terplan (54:44).</div>
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<span style="font-size: x-small;"><b>Notes: </b>the data I used for this are the 2006-2010 5-year ACS tract-to-tract commuting file, published in 2013. Patterns may have changed a little since then, but I suspect they are very similar today, possibly with more congestion. There are severe data warnings associated with individual tract-to-tract flows from the ACS data but at the aggregate level they provide a good overview of local connectivity. I used QGIS to map the flows. I actually mapped the entire United States this way, but that’s going into an academic journal (I hope). I used Michael Minn’s MMQGIS extension in QGIS to produce the animation frames and then I patched them together in GIMP (gifs) and Camtasia (for the mp4s), with IrfanView doing a little bit as well (batch renaming for reversing file order). Not quite a 100% open source workflow but that’s because I just had Camtasia handy. The images are low res and only really good for screen. If you’re looking for higher resolution images, get in touch. It was <a href="https://twitter.com/senerebru" target="_blank">Ebru Sener</a> who gave me the idea to make the dots go back to their original location. I think this makes more sense for commuting data.</span></div>
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<span style="font-size: x-small;"><b>The Cartographatron:</b> Information and images on the 'Cartographatron' used in the Chicago Area Transportation Study (1959) are shown below.</span></div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQhVf_VFIIsnU1N6DV4RyGys509P4dJeUTRKStGRlA2eP2adJjL0mw3UyVk6miqSsbXmd4pOLIpvyHLsTlvim8KU4I9Efdu139xCKFJ4MQJU_dkJ0ZjzE9dAb4yuUN0Q1FazR3eczNuJE/s1600/cartographatron1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiQhVf_VFIIsnU1N6DV4RyGys509P4dJeUTRKStGRlA2eP2adJjL0mw3UyVk6miqSsbXmd4pOLIpvyHLsTlvim8KU4I9Efdu139xCKFJ4MQJU_dkJ0ZjzE9dAb4yuUN0Q1FazR3eczNuJE/s1600/cartographatron1.png" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">From p.39 of CATS, 1959, Vol 1</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizIw4vI7bHeAABzwe7h2ZXoPKS-lu4eSh99XZcSuN375cYzFXFhOpCKpQcCTfrLWH9HK0grHR6SPfFBM28YgQ7WOAe5cqI3vty2oAeecKetxD4KNAe1V2FzHKt_tSp5up7pY85wJknCG0/s1600/cartographatron2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizIw4vI7bHeAABzwe7h2ZXoPKS-lu4eSh99XZcSuN375cYzFXFhOpCKpQcCTfrLWH9HK0grHR6SPfFBM28YgQ7WOAe5cqI3vty2oAeecKetxD4KNAe1V2FzHKt_tSp5up7pY85wJknCG0/s320/cartographatron2.png" width="250" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">From p.98 of CATS, 1959, Vol 1</td></tr>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-72264249815126428692015-06-22T12:37:00.004+01:002015-06-23T06:59:02.677+01:00Where is all London's new housing?<div style="text-align: justify;">
Some of my recent work on housing markets, mortgage lending and housing search has led me to consider the question of where, exactly, London's new housing is located. On a recent visit to King's Cross I was amazed by the sheer scale of development, particularly all the new flats. Because I've been working with the data for another project - and recently re-examined it for a project proposal which explicitly <i>didn't </i>focus on London - I thought it would be interesting to see whether my perception of the flats boom is based in reality. Of course it is! </div>
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The maps below are based on all new build homes sold in London from 1 June 2010 to the end of April 2015 (the most recent data). During this time, according to HM Land Registry 'price paid' data, there were 42,938 transactions on 42,813 properties. This indicates that quite a few properties are not being picked up in this dataset - e.g. compare it to the <a href="http://data.london.gov.uk/housingmarket/#completions" target="_blank">completions data</a> from the London Datastore. Nevertheless, the patterns and distribution of property types is revealing. 88.8% of transactions were for flats, 7.1% for terraced houses, 2.4% for semi-detached properties and 1.7% for detached houses.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgMGQGmnlPZ-tLGhjEM1Es2Edw_Y1LDIrjkgO9iGJJ-yGvDPuXECwP5bCLJkE-Gy_fES6pxhxLJ6BwWJPNFpRsCF5Ws_vmbIUxxXZ9OUHLa-OQfayPTw2QjuYchuZuu41lUjjI1RtPn4Rc/s1600/2010-2015_all_correct.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgMGQGmnlPZ-tLGhjEM1Es2Edw_Y1LDIrjkgO9iGJJ-yGvDPuXECwP5bCLJkE-Gy_fES6pxhxLJ6BwWJPNFpRsCF5Ws_vmbIUxxXZ9OUHLa-OQfayPTw2QjuYchuZuu41lUjjI1RtPn4Rc/s320/2010-2015_all_correct.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">All property types</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgORBD5E94Un_EvmtkUVjrT-z7vgeJQZyfWgGSGUW8uJ6zKK8k9Mbc7xe7CpzpwMIqKiHLV9x80y7gT6krgtDigNrquU6kTe7O6IB2xcMjBP6lnXMpb2dLvYRixbisFQkOMdGbcfwUir4A/s1600/2010-2015_FLATS_correct.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgORBD5E94Un_EvmtkUVjrT-z7vgeJQZyfWgGSGUW8uJ6zKK8k9Mbc7xe7CpzpwMIqKiHLV9x80y7gT6krgtDigNrquU6kTe7O6IB2xcMjBP6lnXMpb2dLvYRixbisFQkOMdGbcfwUir4A/s320/2010-2015_FLATS_correct.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Flats</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgHunwlDC5cqaNcwAtZd7lIpa6BQZoe4WDNoxffPg1aL7kL3ec15Wymrs881v5CrE5MCGEFS61hsHLS3V0DtYvu1gccpacmezi9AF2puIFqQEmv4_lAl8djEalsCfY-Xo0BnwzbTKwHdW0/s1600/2010-2015_TERRACED_correct.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgHunwlDC5cqaNcwAtZd7lIpa6BQZoe4WDNoxffPg1aL7kL3ec15Wymrs881v5CrE5MCGEFS61hsHLS3V0DtYvu1gccpacmezi9AF2puIFqQEmv4_lAl8djEalsCfY-Xo0BnwzbTKwHdW0/s320/2010-2015_TERRACED_correct.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Terraced houses</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi0lmNmtKZHJN6F1Re1qCCJb_vudWgHzvC90AOHmmu9_ElsIwrZMrEZ5YNMOXQZpofzc6bwZjNxKKbeukjhEs04zhksjCqnh3uYQX40oHYe6LEBNB4oMHglj1nITSPTfJiUKRHzUybGlv0/s1600/2010-2015_SEMI_correct.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi0lmNmtKZHJN6F1Re1qCCJb_vudWgHzvC90AOHmmu9_ElsIwrZMrEZ5YNMOXQZpofzc6bwZjNxKKbeukjhEs04zhksjCqnh3uYQX40oHYe6LEBNB4oMHglj1nITSPTfJiUKRHzUybGlv0/s320/2010-2015_SEMI_correct.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Semi-detached houses</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjGbnTQMNry6wdFTMOUBfqmL80iVwrtT3sFupBfYhvkC0niib4yTh_QnJmTP4vS9iDR0EqbQLEw0KJ9LIWUaUW-f7adzxhSzh2BvN4_KTcQK_R6RYa6NNm-HHusQUallRUkUXPmZVFYpb0/s1600/2010-2015_DETACHED_correct.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjGbnTQMNry6wdFTMOUBfqmL80iVwrtT3sFupBfYhvkC0niib4yTh_QnJmTP4vS9iDR0EqbQLEw0KJ9LIWUaUW-f7adzxhSzh2BvN4_KTcQK_R6RYa6NNm-HHusQUallRUkUXPmZVFYpb0/s320/2010-2015_DETACHED_correct.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Detached houses</td></tr>
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Clearly, the mix of new housing - and its relative low volume - is something that many people have commented on before, but I've not seen many people look at the geographical distribution in this way. The important questions arising from these maps - as ever - is why are things the way they are? That's something the maps can't tell us but it does provide an interesting starting point for debate. The discrepancy between the Land Registry data and data on completions is also not surprising owing to the way new build housing is sometimes sold, but it would be interesting to explore this more in future. If you do happen to have a few million quid to spare, good luck finding a new detached London house to live in!</div>
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<b>A note on the maps... </b>I've geocoded the price paid data using Ordnance Survey's Code-Point Open dataset, which can match sales to <a href="http://www.ons.gov.uk/ons/guide-method/geography/beginner-s-guide/postal/index.html" target="_blank">postcode units</a>, rather than street addresses. The transparent bubble map is of course far from perfect but I've used it here to convey the scale and location of new housing, rather than to offer a precise fix. So long as it gives the impression of there being a massive splodge of newbuild flats in Central London that'll do for now. I am aiming to highlight the general scale and geography of development as a fairly quick experiment to see what might be done with the data. No plans to make it interactive (<i>update:</i> the best laid plans of... see map point datadump below).<br />
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<iframe allowfullscreen="" frameborder="0" height="425" mozallowfullscreen="" msallowfullscreen="" oallowfullscreen="" src="https://alasdair.cartodb.com/viz/3a2daa3e-18fb-11e5-9b8b-0e8dde98a187/embed_map" webkitallowfullscreen="" width="100%"></iframe>
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<span style="font-size: x-small;"><b>Update (1715, 22 June 2015): </b>I fixed the glitches, which were caused by a rogue space here and there in the codepoint open file. Moral of the story? Build more houses (I think). Always a giveaway when there aren't many dots in Wandsworth. The numbers were correct all along though. Finally, I've added in some information from HM Land Registry on properties not included in the price paid data.</span><br />
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe_eF2Qj4tRs7yC-jv0N_FhNRH27Y65APj0kA73HkhHdX8oblt9cG7i5-An3eT-Ye5kQvT9N61n0E3gvcGYaH62LwySR_-j3qEhdbjMfJRSuETYdZb2oyV0LC-ENwGEfIkG1tLIw-8Koc/s1600/landreg_definition.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="309" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhe_eF2Qj4tRs7yC-jv0N_FhNRH27Y65APj0kA73HkhHdX8oblt9cG7i5-An3eT-Ye5kQvT9N61n0E3gvcGYaH62LwySR_-j3qEhdbjMfJRSuETYdZb2oyV0LC-ENwGEfIkG1tLIw-8Koc/s320/landreg_definition.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Data excluded from Price Paid dataset - <a href="https://www.gov.uk/about-the-price-paid-data" target="_blank">link</a></td></tr>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-87111878740801339002015-06-19T09:36:00.001+01:002015-06-19T18:13:00.953+01:00Creating an English green belt atlas<div style="text-align: justify;">
<span style="font-size: x-small;"><b>UPDATE: </b>I've fixed the glitches in version 1 and compiled a spreadsheet with the data. See new download at the bottom of the post.</span><br />
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I've blogged <a href="http://www.undertheraedar.com/2012/01/englands-green-belt-closed-data.html" target="_blank">before</a> about <a href="http://www.undertheraedar.com/2015/03/static-maps-from-cartodb.html" target="_blank">green belt</a>, and also written about the underlying data <a href="http://www.theguardian.com/news/datablog/2012/aug/20/green-belt-mapping" target="_blank">in the press</a>. Now that the data are open, I've finally got round to finishing a little project I meant to complete ages ago. I was prompted to do this during a recent visit to my department by <a href="https://twitter.com/drbobbarr" target="_blank">Prof Bob Barr</a>, a legend in the data and GIS worlds. Bob said it would be good to know what percentage of the land area in <a href="https://www.gov.uk/government/statistics/local-authority-green-belt-statistics-for-england-2013-to-2014" target="_blank">each local authority</a> in England was covered by green belt. I agree, so here are the results of my analysis (using 2014 green belt data) from Version 1 of my English green belt 'atlas' (actually lots of individual images to keep the file size down). Here's a snapshot of one of the maps...</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSPoSFYcLrYCF-MXq7XH_DFal_rSsZfgVKnZJBfOuXQGTGdG1BCQRZ0zIKKoMjFgk_pgXXUI9mfhkUfNwqLjav9Vn0K-0mqhwZViWMJhiB8nZt3VlagPS8zrg2sVm4dzzIg-7UqYihdGU/s1600/cheshire+east_greenbelt_2014.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhSPoSFYcLrYCF-MXq7XH_DFal_rSsZfgVKnZJBfOuXQGTGdG1BCQRZ0zIKKoMjFgk_pgXXUI9mfhkUfNwqLjav9Vn0K-0mqhwZViWMJhiB8nZt3VlagPS8zrg2sVm4dzzIg-7UqYihdGU/s320/cheshire+east_greenbelt_2014.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Green belt land in Cheshire East</td></tr>
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And another, this time from Birmingham. You can see that I've dimmed the background so that you can get a sense of other green belt land in the areas I've mapped.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgLW9rMeTUkZXr-2MogG1_VjFEXl2Kx8lZ9_fEkhq_g2sd1Ib9DAv8-6FbcpOUA_ENCQuvQcTTdY5S0K-_9sgvJRqFZTbH6-aSB09vD8GW-oLiDnqKOzmrgb0E8Chqk7h9FNsm3ZOD-qVk/s1600/birmingham_greenbelt_2014.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgLW9rMeTUkZXr-2MogG1_VjFEXl2Kx8lZ9_fEkhq_g2sd1Ib9DAv8-6FbcpOUA_ENCQuvQcTTdY5S0K-_9sgvJRqFZTbH6-aSB09vD8GW-oLiDnqKOzmrgb0E8Chqk7h9FNsm3ZOD-qVk/s320/birmingham_greenbelt_2014.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Birmingham green belt land</td></tr>
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Finally, a few more from around the country...</div>
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There are some glitches in the data but my initial overview suggests the numbers are pretty accurate (see exceptions below). I hope that people might find these maps useful. If you want to use any of them, be my guest.</div>
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Download all the files here (154MB): <a href="https://drive.google.com/file/d/0B0kRhiw4fD7uVTlMdlhfZ1RvbXc/view?usp=sharing" target="_blank">Green Belt Atlas 2014 (version 2)</a> (186 individual map files, plus spreadsheet)<br />
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Download just the spreadsheet: <a href="https://drive.google.com/file/d/0B0kRhiw4fD7uYmRXUjJVVGxlM1k/view?usp=sharing" target="_blank">percent green belt figures</a> for each of the 186 local authorities:<br />
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgj8dgr-8_fwyUs2_ngTeM_245NeSGp2gmMHh1by2a5SNembwv3LvtEVvjK-GmBnnbYbiHwSygWmlu7eD4Z73-p1eNIOyj92BMof0q9hvjUyrQ_ZFSPZkj7Nqu7cTU3Nor_AJHOGRTHE5s/s1600/gb_spreadsheet.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="165" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgj8dgr-8_fwyUs2_ngTeM_245NeSGp2gmMHh1by2a5SNembwv3LvtEVvjK-GmBnnbYbiHwSygWmlu7eD4Z73-p1eNIOyj92BMof0q9hvjUyrQ_ZFSPZkj7Nqu7cTU3Nor_AJHOGRTHE5s/s320/gb_spreadsheet.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Contents of the spreadsheet (download above)</td></tr>
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<b>Warnings:</b> A couple of issues with version 1... 1. The West Lancashire greenbelt area extends into the sea on the <a href="http://data.gov.uk/dataset/english-local-authority-green-belt-dataset/resource/6688dc70-0914-4df8-b1b4-c31eece5568b" target="_blank">green belt shapefile</a> available from DCLG, so the figures here are incorrect (working on a fix). 2. The figure for Ashfield is clearly wrong - not sure why, so I will fix that too. 3. Some areas have extremely low values and may not actually be in the green belt - it may instead be down to the accuracy of underlying data. 4. Mole Valley currently missing, am looking into why. <b><span style="color: red;">UPDATE:</span></b> I looked again at the original Green Belt shapefile from DCLG and found that Mole Valley had the same code as Ashfield, so I fixed that and there's now a map for Mole Valley. New Forest was also assigned two different codes, so I've fixed that too. Also, in the percent figure, I've exluded the part of the West Lancashire green belt that is not on land, so this gives an accurate figure now. You can see from the image below that part of the green belt goes into the Ribble Estuary.<br />
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimwjYAhwAnQPn0JOZLQOc6gGF_a0QhnCEwdArpcA93Lfts6ljqxXu2NOEbZNhy1IJCrz0BNWyZ7lVPu2sw0Ghk41eesrnxcVa1A1Fz2K-Fc2sdmvBHwNjkp6mji0G2NgGMfsY6072ZN-s/s1600/west+lancashire_greenbelt_2014.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" height="192" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEimwjYAhwAnQPn0JOZLQOc6gGF_a0QhnCEwdArpcA93Lfts6ljqxXu2NOEbZNhy1IJCrz0BNWyZ7lVPu2sw0Ghk41eesrnxcVa1A1Fz2K-Fc2sdmvBHwNjkp6mji0G2NgGMfsY6072ZN-s/s320/west+lancashire_greenbelt_2014.png" width="320" /></a></div>
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<b>Technical stuff:</b> I did this in QGIS 2.8 (open source GIS software) using the Atlas tool and a very heavy laptop, plus a bit of trickery I picked up here and there. I blogged about this before, with <a href="http://www.undertheraedar.com/2014/11/automatic-map-production-with-qgis.html" target="_blank">a little tutorial</a>. Perhaps I should actually be using the term 'green belts', as <a href="https://twitter.com/richardblyth7" target="_blank">Richard Blyth</a> pointed out, but forgive me for this.<br />
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-23605103364894100472015-06-03T13:58:00.001+01:002015-06-03T13:58:37.614+01:00The beating heart of the City of London<div style="text-align: justify;">
I've had a rush of blood to the head so here I am with a second blog in two days. I'm getting some slides ready for tomorrow's <a href="http://landor.co.uk/modellingworld/2015/home.php" target="_blank">Modelling World 2015</a> talk in London, which is all about visualising mobility (see below) so I wanted to add in a couple of new visuals on commuting in and out of London. Visualisation can often be just a lot of fancy graphics. This can be useful in itself for a number of reasons (e.g. capturing attention on an important issue, drawing attention to unusual patterns in a dataset) but since I've been working with commuting data in England and Wales I wanted to focus on flows into and out of the City of London. </div>
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This interests me for a number of reasons, including <b>i)</b> commuting can play a significant role in wealth creation and it also needs to be understood in relation to how we measure GVA; <b>ii)</b> commuting is often very stressful and damaging to the individual - particularly long commutes - so I'm interested in the kinds of distances involved and this can be seen easily on a map; <b>iii)</b> commuting can often be environmentally damaging - though this isn't what I'm mapping here; <b>iv)</b> commuting in and around London is often about green belt hopping so I was curious to see how much commuting comes from beyond the metropolitan green belt; and <b>v)</b> commuting is a two-way process and affects places at both ends and in between due to travel. </div>
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So, here's what I did. I took the MSOA-level commuting data for England and Wales (table WUEW01 <a href="https://www.nomisweb.co.uk/census/2011/origin_destination" target="_blank">here</a>), used a bit of QGIS, extracted frames from QGIS using the MMQGIS plugin, then patched it all together in GIMP to create an animated gif. One for inflows, one for outflows and one for in and outflows (thanks to <a href="https://twitter.com/senerebru" target="_blank">Ebru Sener</a> for the idea). It might run a little slowly in the blog post in a browser but see below for the images. Just to clarify, I've only shown flows of 25 or more into the City of London. Those not familiar with the data should be aware the the 'City of London' refers to the small area in the centre of London and not the entirity of Greater London! An obvious point but one worth repeating in case anyone is confused. A Greater London map would have many more data points, covering most of England.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNmONZdNBCJdbYb28UlGFSHr2yn7xea-hDXASeDThPZy059oCYFb3gdv__nkiArjUSWC4V0elBScFZWYM0nu0DtLxF7m_3jcfsygMPvE5VoIxx4nH032fEzW2xNj3yXIGcHs4y_eK6ewk/s1600/intocity6.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiNmONZdNBCJdbYb28UlGFSHr2yn7xea-hDXASeDThPZy059oCYFb3gdv__nkiArjUSWC4V0elBScFZWYM0nu0DtLxF7m_3jcfsygMPvE5VoIxx4nH032fEzW2xNj3yXIGcHs4y_eK6ewk/s320/intocity6.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Commuting flows (>=25) into the City of London</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheclrpE6lqB32YsOT7MPtm1kYWTxvmnfISVE6LO-126FvGlhIHS-hYZyp2uXy0mwqPRK7FPERy18ZqElPu6g53Epu-JGTJNqdsaSNrdCEGc3DCjlkXWhtHRcsS1pVgbiuwoxuxGd1bKKA/s1600/outofcity1.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheclrpE6lqB32YsOT7MPtm1kYWTxvmnfISVE6LO-126FvGlhIHS-hYZyp2uXy0mwqPRK7FPERy18ZqElPu6g53Epu-JGTJNqdsaSNrdCEGc3DCjlkXWhtHRcsS1pVgbiuwoxuxGd1bKKA/s320/outofcity1.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Same as above, but going back the way</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiYXoRuCf5o-FLwCE4q7PYljGJCc0IR-IE2nEOf6uhNVo-q03w9dthMKE5zX2Mim9CAYbWcBDwKfNWWq7vXbT6wQl4E5d4xwpSea_RMXUklkIRQne9vVdQbV21xqkzI3VQx4HxCP23B55g/s1600/inoutcity4.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="193" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiYXoRuCf5o-FLwCE4q7PYljGJCc0IR-IE2nEOf6uhNVo-q03w9dthMKE5zX2Mim9CAYbWcBDwKfNWWq7vXbT6wQl4E5d4xwpSea_RMXUklkIRQne9vVdQbV21xqkzI3VQx4HxCP23B55g/s320/inoutcity4.gif" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The 'pulse' of the City of London</td></tr>
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You should be able to get a better view of the images by clicking on them individually and if you want them to work more quickly try saving them to your own machine.</div>
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<br />Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-15322993760850865222015-06-02T10:24:00.000+01:002015-06-02T10:24:30.377+01:00The Polycentric South East<div style="text-align: justify;">
Tweets yesterday from <a href="https://twitter.com/michaellondonsf" target="_blank">Michael Edwards</a> and <a href="https://twitter.com/JosephPKilroy/status/605355091923767297/photo/1" target="_blank">Joseph Kilroy</a> reminded me of a map I produced last year in which I showed commuting patterns in South East England, minus London. I did this to get a sense of the <a href="https://www.google.co.uk/search?q=polycentric+south+east+england+commuting&rlz=1C1CHFX_enGB518GB518&oq=polycentric+south+east+england+commuting&aqs=chrome..69i57.6175j0j1&sourceid=chrome&es_sm=122&ie=UTF-8" target="_blank">polycentric</a> nature of travel to work in the South East as this has been a topic of many previous studies - including the famous <a href="https://books.google.co.uk/books?id=vhelHHnagCsC&lpg=PR7&ots=hiIv3bngAo&dq=polycentric%20south%20east%20england%20commuting&pg=PP1#v=onepage&q=polycentric%20south%20east%20england%20commuting&f=false" target="_blank">Hall and Pain</a> book - but none (to my knowledge) using the 2011 Census data I mapped. The other reason for me blogging about this today is that I'm speaking on a similar topic at <a href="http://landor.co.uk/modellingworld/2015/home.php" target="_blank">Modelling World 2015</a> this Thursday in London. Enough words, time for some maps, which I've refreshed for this week.</div>
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The first map below shows all commuting in the South East of England in 2011, without place names. As you can see, I've removed London from the equation, both in relation to travel to work flows and from the underlying map canvas. This gives a slightly different perspective than the one we're used to. The second map is the same as the first but I've added the names of local authorities in order to help identify places. Click any of the images to enlarge.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge_jJux5mHP22foLlR_Gi9nagCr1xvo5gm-umATLFQtfhj_0bjOL5KgnuAnZXxu29PHEmBv1zkL1gcBfNSrg0UB75Pr4ALdixpmSVZ3leUo92LfqoBld0I08r8RhMJ3VW_ddht98hZcpc/s1600/nonlon.jpeg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEge_jJux5mHP22foLlR_Gi9nagCr1xvo5gm-umATLFQtfhj_0bjOL5KgnuAnZXxu29PHEmBv1zkL1gcBfNSrg0UB75Pr4ALdixpmSVZ3leUo92LfqoBld0I08r8RhMJ3VW_ddht98hZcpc/s320/nonlon.jpeg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Commuting in South East England, 2011</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhtIRB0NNHovaOK_JfNYbLJ31KDJE_3clwombjc9rIRaQS-Ib7b51xhitbYZcHF68JvqUWEmofu7hkuZlWHcB5XNm-Zsbw0AApRn60KcScnEcEvzN12W7KLXXiJzMVQRrq4HT41VXA1iis/s1600/nonlon-labels.jpeg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhtIRB0NNHovaOK_JfNYbLJ31KDJE_3clwombjc9rIRaQS-Ib7b51xhitbYZcHF68JvqUWEmofu7hkuZlWHcB5XNm-Zsbw0AApRn60KcScnEcEvzN12W7KLXXiJzMVQRrq4HT41VXA1iis/s320/nonlon-labels.jpeg" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Same as above, but with labels</td></tr>
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Now, here's what it looks like when you add London back in... Kind of brings to mind astronomical metaphors, as hinted at in <a href="http://www.rtpi.org.uk/media/6003/Uniting-Britain.pdf" target="_blank">a previous study by the RTPI</a>. I should add that the definition of a supernova is 'a star that suddenly increases greatly in brightness because of a catastrophic explosion that ejects most of its mass' so this might be stretching things slightly... Then again, if what people are saying about the displacement of the poor from London this might actually be spot on.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-GJaMGY-oCmyukZZqb3GKHpcRph7wZW1eXvgFg8srZ-Uy2OYSExYjBTDyChwAi6lNrJvlkePjV7fg3tv1QEIsoeTmM0h2h2aP3huSib1Z8rBsuy23pSpGTM9iNA9PVPHgOFLgYnL41JA/s1600/lon-nolabels.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi-GJaMGY-oCmyukZZqb3GKHpcRph7wZW1eXvgFg8srZ-Uy2OYSExYjBTDyChwAi6lNrJvlkePjV7fg3tv1QEIsoeTmM0h2h2aP3huSib1Z8rBsuy23pSpGTM9iNA9PVPHgOFLgYnL41JA/s320/lon-nolabels.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The 'London Supernova'</td></tr>
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<br /><br />Finally, I've produced a zoomed-in version closer to London where you can see some of the flows which go through/over the capital. I don't fancy that commute!<div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-67552644866962534332015-05-12T21:38:00.003+01:002015-05-12T21:47:43.521+01:00The 2015 General Election: London Results<div style="text-align: justify;">
The perennially excellent London DataStore <a href="http://data.london.gov.uk/dataset/general-election-results-2015" target="_blank">has published</a> comprehensive, accessible and usable data on the 2015 General Election. So, naturally, I had to make some maps of it. There probably <a href="http://www.bloomberg.com/graphics/2015-uk-election/messy.html" target="_blank">isn't anything</a> about this election that hasn't been mapped but since my <a href="http://www.undertheraedar.com/2015/05/can-google-search-data-predict-election.html" target="_blank">last blog</a> was a General Election piece I thought I'd do a little follow-up, with not a hexagon in sight. There have been <a href="http://www.cityam.com/215414/general-election-2015-results-heres-who-came-second-every-seat-including-120-silver-medals" target="_blank">quite</a> <a href="http://kieranhealy.org/blog/archives/2015/05/09/who-came-second-in-the-uk-election/" target="_blank">a few</a> 'who came second' maps but not many which include third and fourth places. I'm particularly interested in London because it's something of an exception in the South East of England and, well, I just wanted to make some maps. Below you'll see maps for who came first, second, third and fourth. The last map has the constituency names. I resisted the temptation to do a 'who came eleventh' map, but, since you asked, there were only four constituencies where there were at least 11 candidates, and the parties included the Whig Party. They might have been quite prominent had these maps been made in 1830 (incidentally, there were 658 constituencies in the UK then, which only had 24 million people).</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfdrXXe5rUsXsorB5IZOqfl6XHj2QarIQABXhq_07L-UEeGZlP2RLUB9FWGUvxsDVO0x5FZW0vST6RGW5ZIAcHDdN67n8HuxMlNoZuzJR3Y2DpV-9hJbbEADPpRrY9Fci06xBd-PA3HE4/s1600/london_rank1.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjfdrXXe5rUsXsorB5IZOqfl6XHj2QarIQABXhq_07L-UEeGZlP2RLUB9FWGUvxsDVO0x5FZW0vST6RGW5ZIAcHDdN67n8HuxMlNoZuzJR3Y2DpV-9hJbbEADPpRrY9Fci06xBd-PA3HE4/s320/london_rank1.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">'That's Blockbusters' - for Labour</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhdeDjrD_PFyUv2dmTH5Y7OqBEkyiLVzl5gstjm41xUdJ_4lRVhHH78bNJZK5CWAzppLYAEfcoxntwQYrdawAAUlwWHEEwqqrGJZIcvEt0A5euA0ZFwc0NQDh5vECFfkIO0g75xTH5ZNk/s1600/london_rank2.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjhdeDjrD_PFyUv2dmTH5Y7OqBEkyiLVzl5gstjm41xUdJ_4lRVhHH78bNJZK5CWAzppLYAEfcoxntwQYrdawAAUlwWHEEwqqrGJZIcvEt0A5euA0ZFwc0NQDh5vECFfkIO0g75xTH5ZNk/s320/london_rank2.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">UKIP emerge and Tories dominate second place</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh_B-VAHBmD4HJmobJ2Ck0zZHLx1chN_DqAo54UZoCTbSWVGfUj7kvfIu5qUnBkuLUysDx8_7ESyjOWS9JrreOG1XFt5Op7BKgJtZwDqnLLgEwvzXjxCfSBsf9qFCNVzTSR5jSXhsWTvAc/s1600/london_rank3.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh_B-VAHBmD4HJmobJ2Ck0zZHLx1chN_DqAo54UZoCTbSWVGfUj7kvfIu5qUnBkuLUysDx8_7ESyjOWS9JrreOG1XFt5Op7BKgJtZwDqnLLgEwvzXjxCfSBsf9qFCNVzTSR5jSXhsWTvAc/s320/london_rank3.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">UKIP by far the most in third place - Greens emerge</td></tr>
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<tr><td class="tr-caption" style="text-align: center;">No place for three 'main' parties here</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjNudgsD4lqVfomFT-ch-kMdmZiQLRpzweqgHgWjzd7ajQQULs7d5Jy2f9_7MvHbhxmjTYu-mQ9lmWesxsr5nQZr66-pFryISh4XnLgcVerVARPjONY8vFRoM3vXQPLNndXw46H9dOkes0/s1600/london_winners.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="226" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjNudgsD4lqVfomFT-ch-kMdmZiQLRpzweqgHgWjzd7ajQQULs7d5Jy2f9_7MvHbhxmjTYu-mQ9lmWesxsr5nQZr66-pFryISh4XnLgcVerVARPjONY8vFRoM3vXQPLNndXw46H9dOkes0/s320/london_winners.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Just in case you don't know all constituencies off by heart</td></tr>
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You should be able to see pretty big versions of the maps if you click on them and then open them in a new tab/window. I've dispensed with the usual boring map legend and instead turned it into a 'bargend' (a portmanteau I just invented). I hope you find these interesting. </div>
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Final nugget: the Whig Party came 9th in Bethnal Green and Bow (their best result) with 203 votes for my namesake, Alasdair Henderson.</div>
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<br />Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-30696280125873227392015-05-07T16:08:00.002+01:002015-05-07T16:13:49.372+01:00Can Google search data predict an election victory?<div style="text-align: justify;">
Today seems like a good day to write a little blog post on what search data can and cannot tell us. Why? Because of the <a href="http://www.dailymail.co.uk/sciencetech/article-3070470/Google-Search-tips-Cameron-win-election-Nigel-Farage-s-Ukip-beat-Labour-Liberal-Democrats.html" target="_blank">story below</a>, which has been on the front page of the MailOnline for much of the day. This is just the way news works, but I thought it would be useful to give a bit more information here. The story behind the story goes something like this...</div>
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<a href="https://twitter.com/smfrogers" target="_blank">Simon Rogers</a>, datajournalist and Data Editor at Google in San Francisco, got in touch some time in April to ask if I could help him map party leader search patterns by constituency. I'd been doing a lot of work with <a href="http://www.tandfonline.com/doi/full/10.1080/02673037.2014.974142" target="_blank">search data for housing markets</a> anyway so this seemed like an interesting idea. We took search data for all points that were geocoded (there were about 5,000 total across the UK) and then produced a constituency version for all 650 seats. The final constituency results matched very closely the proportions for the individual places. The data are for the previous 12 months. </div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhisVeVEUxhSNls7DeqGQLKG74YvA1EzPnRyuQ0YG9AW9lguiWRpRRbd_UNdtT_mCQbsI_Teu1hQodAy9UGDrlDaviyCqIhdkWsndSDbOK0bBoCoRHSe_Yyck-6sWpCpgwHWu03o9zfGRU/s1600/google_leader_search.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhisVeVEUxhSNls7DeqGQLKG74YvA1EzPnRyuQ0YG9AW9lguiWRpRRbd_UNdtT_mCQbsI_Teu1hQodAy9UGDrlDaviyCqIhdkWsndSDbOK0bBoCoRHSe_Yyck-6sWpCpgwHWu03o9zfGRU/s320/google_leader_search.png" width="206" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">MailOnline front page 07/05/15</td></tr>
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The big question is what this all means. Do I think, as the MailOnline suggest, that 'Google Search tips Cameron to win election'? No. Do I think it disproves it? No. Do I think the large volume of search for Nigel Farage indicates his level of popularity across the country? Again, no. However, it could indicate that people are more likely to show interest in UKIP in an environment when nobody else is watching or listening. But we don't know. Does this prove that Miliband will come third? Definitely not. The map merely indicates who was the most searched for party leader in each constituency. The intent and sentiments of individual users are not known. In my own research in housing market analysis I've tackled this by doing interviews with website users but since this data is from Google they could of course add in other terms which people might combine with party leader names (some more favourable than others!). </div>
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<a href="https://twitter.com/Katienew" target="_blank">Kate Newton</a> from Bing also got in touch to say they had worked on <a href="http://blogs.bing.com/uk/2014/09/03/bing-predicts-forecasts-the-scottish-independence-referendum-in-uk-test/" target="_blank">something similar</a> (though much more sophisticated) in relation to the Scottish Independence referendum last year. More widely, there is a body of <a href="http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2022293" target="_blank">emerging research</a> (including my own) which looks at search patterns and subsequent activity - mostly in the field of economics. The results suggest that search can be analysed meaningfully to predict future activity. But that's not what the party leader piece was about - not from my perspective. Thankfully, other media outlets were more measured in their analysis - such as <a href="http://www.buzzfeed.com/tomphillips/google-election-maps#.jaMxao6BP3" target="_blank">BuzzFeed UK</a>, <a href="http://www.scotsman.com/news/uk/sturgeon-tops-scots-google-searches-for-leaders-1-3765243" target="_blank">The Scotsman</a>, and <a href="http://www.telegraph.co.uk/news/politics/conservative/11584038/Conservatives-top-Google-searches-by-constituency-but-not-by-enough-for-a-majority.html" target="_blank">The Telegraph</a>. </div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8smH7KfdFsS7lP_-JpwcdZ2Vqb12nV_Mda_BOVJ2ZXW0QVhgrFMGrb6pEUhSGQtaly9fOn3wlYiWUCNPoKXSqCxqPM7dIoChVwjWeZROKnqBPlWX-NJB6Ac8sls9IEUL-uxX7EA7HFpk/s1600/google_leader_search_daily_mail.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg8smH7KfdFsS7lP_-JpwcdZ2Vqb12nV_Mda_BOVJ2ZXW0QVhgrFMGrb6pEUhSGQtaly9fOn3wlYiWUCNPoKXSqCxqPM7dIoChVwjWeZROKnqBPlWX-NJB6Ac8sls9IEUL-uxX7EA7HFpk/s320/google_leader_search_daily_mail.png" width="273" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">MailOnline story 07/05/15</td></tr>
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What's most interesting to me? Well, I'm most interested to see how the search patterns relate to outcomes in <a href="http://www.cityam.com/215221/where-are-2015-general-elections-most-marginal-seats-closest-constituencies-mapped" target="_blank">key marginals</a>. I suspect there will not be much of a pattern but if there is it will be interesting to attempt to take this little piece of work further - perhaps for the US 2016 election. Other than that, this is an interesting stocking filler on a day when the papers and TV crews are forbidden from reporting anything really substantial until the polls close at 10am. In the meantime, my favourite snippets from the search map...</div>
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David Cameron is the most searched for leader in his own constituency, but he's surrounded by a sea of purple, plus a blob of red and orange.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhaF5usVnrYxDQqbQmDiSKQAToX1xk1wpYS5kWrLp7p29cCy2UZMxj8fM1y_3-f0nKyQ4Mf-yqJlAC2gELMxP7tt8yfXHXptFjrFS1kAuA269PuLICejZ9ibW9iXwJjZGEfgBvmPFuO728/s1600/search_cameron_witney.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="320" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhaF5usVnrYxDQqbQmDiSKQAToX1xk1wpYS5kWrLp7p29cCy2UZMxj8fM1y_3-f0nKyQ4Mf-yqJlAC2gELMxP7tt8yfXHXptFjrFS1kAuA269PuLICejZ9ibW9iXwJjZGEfgBvmPFuO728/s320/search_cameron_witney.png" width="264" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Witney - David Cameron's constituency</td></tr>
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Perhaps a little predictably, there is a lot of search for UKIP in Kent but - strangely - it appears that in the constituency where Nigel Farage is standing (Thanet South) the party leader most searched for is Ed Miliband.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiW1UTax1z3ZXsBnK72RogiLVlXk4NeySnj9DVSxir1po2Xi8F34PgBictTXz55ZMySEvh-YsZhhd60bbvo_MNJVZIrdSY5ZyfWDXp7hHr01VQ5HjgD9RPrEM4w-GlPqwZVyuDCyEVb5H0/s1600/search_farage_thanet.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="210" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiW1UTax1z3ZXsBnK72RogiLVlXk4NeySnj9DVSxir1po2Xi8F34PgBictTXz55ZMySEvh-YsZhhd60bbvo_MNJVZIrdSY5ZyfWDXp7hHr01VQ5HjgD9RPrEM4w-GlPqwZVyuDCyEVb5H0/s320/search_farage_thanet.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">UKIP - lots of search in Kent, but not to much in Thanet South</td></tr>
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The search results produce some interesting results. The image below is a good example. Natalie Bennett (Green Party) is the most searched for leader in Durham North West and next door in Durham North the leader (by search over the past 12 months) is Leanne Wood (Plaid Cymru). I suspect this was down to a localised spike in interest after the leaders' debates.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjnsVFXAsuff7TiVodF-LnwJkNZkohcI8JXyZ0vCHV68Fjm1-FqriTf7-hj_zvJ-CeE8PkbG4DrhLDZCnT5MYdV-qWZD1lfXl0elqoKKQfOFw0LikMSKJNc_N-z56NODRuw5xFFXLO4sJM/s1600/search_greens_ne.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" height="307" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjnsVFXAsuff7TiVodF-LnwJkNZkohcI8JXyZ0vCHV68Fjm1-FqriTf7-hj_zvJ-CeE8PkbG4DrhLDZCnT5MYdV-qWZD1lfXl0elqoKKQfOFw0LikMSKJNc_N-z56NODRuw5xFFXLO4sJM/s320/search_greens_ne.png" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Durham - Green and Welsh Nationalist stronghold?</td></tr>
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Other interesting nuggets to emerge were the way in which geographical patterns sometimes reflected the opposite of what you'd expect. The most obvious example was where Nicola Sturgeon (SNP and not standing in this election) was the most searched for party leader in several English constituencies, such as Chesterfield (below). Her excellent performance in the leaders' debates probably led to a spike in interest. Perhaps the SNP ought to consider putting up candidates in England too.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjEUSUkk9awBc3GgVi8UU-vcUJHnB08QwDbymP3IxifTlJfbf5Ih6BXwkaUcN6HVcc_x-LDbwz1x94xi564crBcR3W4hW6ludXd-XayFQf1HgnBtHaP_gwC7qa2wYKSJ4uGXlVYDNE0Rb0/s1600/search_sturgeon_chesterfield.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjEUSUkk9awBc3GgVi8UU-vcUJHnB08QwDbymP3IxifTlJfbf5Ih6BXwkaUcN6HVcc_x-LDbwz1x94xi564crBcR3W4hW6ludXd-XayFQf1HgnBtHaP_gwC7qa2wYKSJ4uGXlVYDNE0Rb0/s1600/search_sturgeon_chesterfield.png" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The SNP take Chesterfield? Not so fast.</td></tr>
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A kind of similar situation to the SNP/Chesterfield example can be seen in the final image below, where Nigel Farage is the most searched for leader in Aberdeen North. This Scottish constituency has no UKIP candidate and, even if it did, they would be a long way away from the top party.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijlURAsNVgWrDjTquHgzxS6yzFXaSo999JjqA9ndvbFJ2JPn_W3K63bgVHBmYvcKYnuVkYEIkYsHNd0wysKsICGyr1ascwZY4fNFTcO-Rn-yQo_J6MioBDx_T35cQEKkTgnAlhBlSLevw/s1600/search_ukip_aberdeen.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEijlURAsNVgWrDjTquHgzxS6yzFXaSo999JjqA9ndvbFJ2JPn_W3K63bgVHBmYvcKYnuVkYEIkYsHNd0wysKsICGyr1ascwZY4fNFTcO-Rn-yQo_J6MioBDx_T35cQEKkTgnAlhBlSLevw/s1600/search_ukip_aberdeen.png" /></a></div>
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What's my prediction for the outcome of the election? The only prediction I'll make is that the results will look nothing like this map!Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-87417920698598149612015-03-01T10:51:00.000+00:002015-03-01T10:55:59.223+00:00Static maps from CartoDB<div style="text-align: justify;">
I've used <a href="http://cartodb.com/" target="_blank">CartoDB</a> quite a bit recently to create interactive maps. My <a href="http://alasdair.cartodb.com/viz/1332c872-a887-11e4-8c45-0e9d821ea90d/embed_map" target="_blank">Historic Buildings of Scotland</a> map and my <a href="http://alasdair.cartodb.com/viz/9d5b6008-aaf9-11e4-b9f7-0e4fddd5de28/embed_map?zoom=14&center_lat=51.5134673&center_lon=-0.1398175" target="_blank">England Grade I Listed Buildings</a> map have both proved popular. Another map that received lots of traffic was my <a href="http://alasdair.cartodb.com/viz/c1925a82-9670-11e4-ab1a-0e853d047bba/embed_map" target="_blank">English Greenbelt</a> map. This one in particular was popular I think because it allowed people to find out exactly where the green belt was near them - or in fact to find out which areas aren't greenbelt. Although interactive maps are great for some things, sometimes we just want to put a static image in a report or on a website and this can often be a bit tricky with interactive content. Luckily, CartoDB allows users to export static image files (png format), and you can customise the dimensions as well. This CartoDB <a href="http://blog.cartodb.com/static-maps/" target="_blank">blog post</a> shows you how - though you may need to disable pop-ups in your browser if it doesn't work. This tool opens up the static map in a new browser tab so if nothing happens check your pop-up blocker settings.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="http://ajrae.staff.shef.ac.uk/img/gb-cdb.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://ajrae.staff.shef.ac.uk/img/gb-cdb.png" height="320" width="247" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">View the <a href="http://ajrae.staff.shef.ac.uk/img/gb-cdb.png" target="_blank">full size</a> version</td></tr>
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As you can see above, I've exported my English Greenbelt map. I often get asked if I have a large static image of it because if you <a href="https://www.google.co.uk/search?q=green+belt+england&espv=2&biw=1280&bih=685&source=lnms&tbm=isch&sa=X&ei=su_yVNXcMYbSaP7jgJgP&ved=0CAcQ_AUoAg#tbs=isz:lt%2Cislt:xga&tbm=isch&q=greenbelt+england&imgdii=_" target="_blank">search online</a> there aren't really any large up to date, decent resolution, detailed green belt images. I also added some attribution information (important!) and a basic title. This is just a quick example so isn't perfect in relation to labels and so on but it gives a simple overview of the green belt.<br />
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-91395530313421261152015-01-25T10:39:00.000+00:002015-01-25T10:39:02.068+00:00How many people live in Tokyo?<div style="text-align: justify;">
Back in August 2014 when I was preparing some material for teaching students how to query data in a GIS, I devised a very simple example where they had to select all the countries in the world with a lower population than the Tokyo Metropolitan Area (or Greater Tokyo Area, as it's sometimes called). I did this just as an example but since I found the results quite interesting, I quickly turned it into a map and posted it on Twitter, complete with 'Toyko' typo in the subheading. It was really just a quick example of how to query data in a GIS but it also highlighted the massive population of the Tokyo metropolitan area. You can find the full size, original image <a href="http://ajrae.staff.shef.ac.uk/img/tokyo-crop.png" target="_blank">here</a>. I was prompted to write this blog because the map was reposted on the Canadian Twitter feed <a href="https://twitter.com/AsapSCIENCE" target="_blank">@AsapSCIENCE</a> a few days ago and since then my inbox has been a bit busy.</div>
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<a href="http://ajrae.staff.shef.ac.uk/img/tokyo-crop.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="http://ajrae.staff.shef.ac.uk/img/tokyo-crop.png" height="215" width="320" /></a></div>
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Now, back to the original question of how many people live in 'Tokyo'. Well, when I say 'Tokyo' in the map, I'm referring to the wider metropolitan area, which in 2014 the United Nations <a href="http://esa.un.org/unpd/wup/Highlights/WUP2014-Highlights.pdf" target="_blank">World Urbanization Prospects</a> said has a total population of 37,833,000, far beyond the next largest urban agglomeration, Delhi, at 24,953,000. By way of comparison, using the urban agglomeration population (rather than a city's administrative boundaries), Toronto had 5.9 million, London had 10.2 million and Beijing had 19.5 million. Clearly, these definitions include other urban places that are not Tokyo (e.g. Yokohama) but they are recognized as being part of a fairly coherent metropolitan area. </div>
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So, in the map, I'm using a figure of 'approx 36 million' as I say but in reality the UN figure is a bit higher. If we want to narrow the definition down to just the inner urban area then obviously the figure reduces significantly. I'm not usually one to cite Wikipedia, but in this case it's a good place to go to learn about the various <a href="http://en.wikipedia.org/wiki/Greater_Tokyo_Area" target="_blank">definitions</a> of the Greater Tokyo Area/Kantō region. If you don't want to click, here's a summary of some Tokyo populations...</div>
<ul>
<li>Former city area (23 'special wards') - 8.95 million people</li>
<li>Tokyo Metropolis - 13.05 million</li>
<li>Tokyo Metropolitan Employment Area - 31.70 million</li>
<li>National Capital Region - 43.47 million</li>
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<span style="text-align: justify;">If we take the metropolitan definition used by the United Nations, then Tokyo does indeed have more people than Canada, at 35.5 million (</span><a href="http://www.statcan.gc.ca/daily-quotidien/140926/dq140926b-eng.htm" style="text-align: justify;" target="_blank">2014 Statistics Canada estimate</a><span style="text-align: justify;">) and far more than Australia at 23.7 million (</span><a href="http://www.abs.gov.au/ausstats/abs@.nsf/0/1647509ef7e25faaca2568a900154b63?opendocument" style="text-align: justify;" target="_blank">see their population clock</a><span style="text-align: justify;">). The Tokyo metropolitan population is roughly the same as the whole of California, which currently stands at about 38 million.</span></div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiVJZM5AgwjGdHQilBS2y2YgC3PG3KKrobnQGIonsoTpsBUodvUkWdU6IZqLYHyYJwiVequ9xhLx9OXRi5nv8xz7zvLkRd7bUSueRnKoPwvvM4BRNpoq66Xz6J0bpO6vkejnyJW-8k4wRI/s1600/california.png" height="231" style="margin-left: auto; margin-right: auto;" width="320" /></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="https://www.google.co.uk/search?q=population+california&oq=population+california&aqs=chrome..69i57.4728j0j4&sourceid=chrome&es_sm=122&ie=UTF-8" target="_blank">Link to chart</a></td></tr>
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<br />This was all just a little bit of map trivia and whilst it seems to have annoyed some people who live in a red country, the point was just to demonstrate the simple analytical power of GIS in addition to the size of Tokyo (to make it more interesting). The data I used are from <a href="http://www.naturalearthdata.com/" target="_blank">Natural Earth</a> if you want to have a look yourself and the software I used is a free GIS called <a href="http://www.qgis.org/en/site/" target="_blank">QGIS</a>, which is really good. Some other random facts about what happened to my original tweet...<div>
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<li>It was <a href="https://twitter.com/guardiancities/status/502770841034444800" target="_blank">tweeted by Guardian Cities</a> and then retweeted 309 times and favourited 107 times.</li>
<li>It was <a href="https://twitter.com/AsapSCIENCE/status/558398789346537474" target="_blank">tweeted by AsapSCIENCE</a> on 22 January 2015 and since then retweeted 96 times and favourited 110 times.</li>
<li>Akihabara News wrote <a href="http://akihabaranews.com/2014/08/27/article-en/tokyo-largest-city-known-universe-and-props-alasdair-rae-1842133282" target="_blank">an entire article about the map</a>, and even spelled my name correctly - that hardly ever happens.</li>
<li>Tokyo Desu <a href="http://tokyodesu.com/2014/08/26/every-country-highlighted-on-this-map-has-a-smaller-population-than-tokyo/" target="_blank">also did a piece on it</a> - and added another map too.</li>
<li>What does it all look like on the ground? This photo (below) from <a href="http://www.atbreak.com/picts/tokyo-from-the-air/" target="_blank">ATBREAK</a> gives you some idea.</li>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPTBGINnuiR1ojrV7MbP-K7Yirqvam5_Jirxgv7TZzouMPCcrS9U2tQGfpQ0iUcd7rGeTrXlHmX_K7czfx8Q5oGMEZ-Wxl-_JMf3op1l5b_qYAghxbvgkenUc8p_yuvksmota5LDt7L6A/s1600/Tokyo-From-The-Air.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPTBGINnuiR1ojrV7MbP-K7Yirqvam5_Jirxgv7TZzouMPCcrS9U2tQGfpQ0iUcd7rGeTrXlHmX_K7czfx8Q5oGMEZ-Wxl-_JMf3op1l5b_qYAghxbvgkenUc8p_yuvksmota5LDt7L6A/s1600/Tokyo-From-The-Air.jpg" height="240" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Tokyo metropolitan area</td></tr>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-72410151956427763572015-01-17T12:44:00.001+00:002015-01-17T12:46:43.913+00:00Interpreting political maps<div style="text-align: justify;">
I recently <a href="https://twitter.com/undertheraedar/status/556373982380036097" target="_blank">tweeted</a> a couple of maps showing the 100 most and least deprived constituencies in England. I used the 2010 English Indices of Deprivation to calculate this, aggregating the data from smaller areas to parliamentary constituencies. The method is not perfect but on the whole the areas identified are either among the poorest or richest in England. There are <a href="http://en.wikipedia.org/wiki/List_of_MPs_for_constituencies_in_England_2010%E2%80%93" target="_blank">533 constituencies</a> in England so the figure of 100 is roughly the 20% most and least deprived (18.76% to be more precise). I shaded the maps using red for Labour, blue for Conservative, Yellow for Liberal Democrats and so on. The most obvious thing about the maps is, of course, the fact that the most deprived map shows nearly all Labour constituencies and the least deprived shows almost all Conservative constituencies. Click the caption below the images to see interactive versions.</div>
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<tr><td style="text-align: center;"><a href="http://ajrae.staff.shef.ac.uk/img/mostdeprived.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://ajrae.staff.shef.ac.uk/img/mostdeprived.png" height="320" width="286" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="http://alasdair.cartodb.com/viz/d81f30fa-9d5e-11e4-ae78-0e9d821ea90d/embed_map" target="_blank">100 most deprived constituencies</a></td></tr>
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<tr><td style="text-align: center;"><a href="http://ajrae.staff.shef.ac.uk/img/leastdeprived.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://ajrae.staff.shef.ac.uk/img/leastdeprived.png" height="320" width="295" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;"><a href="http://alasdair.cartodb.com/viz/898c0d8a-9e23-11e4-ba3a-0e853d047bba/embed_map" target="_blank">100 least deprived constituencies</a></td></tr>
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These kinds of maps often make a big impact and are shared widely but people tend to draw conclusions from the patterns they see that are not necessarily correct - and often conclusion which mirror pre-existing biases and perspectives. For example, some people see these maps and claim that voting Labour makes you poor or that only rich people vote Conservative. Some would even claim that this proves that Labour has failed the constituencies they serve. Opponents would argue that coalition cuts have merely deepened spatial inequalities and hit Labour-voting areas hardest. This is all a bit dramatic, but you don't have to search online long to find such views.<br />
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Other people might say that if you want to be richer you should vote Conservative. Other people would tell you not to be so simplistic and point to the way in which voting patterns are formed at the local level. Still others might point to the longstanding economic differences between north and south in England and say that this has something to do with it. Perhaps others will say that the Conservatives are the party of the rich and that Labour are the party for the poor. There are varying degrees of truth in all these views but the point I want to make here is that none of this can be proven just by looking at a political map.<br />
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For me, such maps are a starting point for a conversation about what these patterns might mean, whether they are a problem and what might be done about it, if anything. I'm not making these maps because I'm pro-Labour or pro-Conservative or because I think that they prove anything in particular but because I want to draw attention to the patterns and what they might mean. Finally, some observations from the maps...<br />
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<li>There are no Labour constituencies amongst the 100 least deprived in England.</li>
<li>There are 2 Conservative constituencies amongst the 100 most deprived in England.</li>
<li>Sheffield Hallam (Liberal Democrat, Nick Clegg) is amongst the 100 least deprived constituencies in England. </li>
<li>There are 5 Liberal Democrat constituencies amongst the 100 most deprived in England.</li>
<li>There are 7 Liberal Democrat constituencies amongst the 100 least deprived in England.</li>
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It will be very interesting to see how these patterns change (if at all) after the General Election this year.<br />
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-80747469053502597042015-01-14T09:39:00.001+00:002015-01-14T09:39:25.971+00:00Visualising Residential Mobility in Urban England<div class="separator" style="clear: both; text-align: center;">
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Last year I produced a few <a href="http://ajrae.staff.shef.ac.uk/img/eng_ttw_all_blue_300px_labels.png" target="_blank">commuting</a> <a href="http://ajrae.staff.shef.ac.uk/img/ew_ttw_rail_2011.png" target="_blank">maps</a> of England and Wales after the 2011 Census data were released. Now I've turned my attention to mapping patterns of residential mobility in urban areas of England as part of my work on understanding housing markets. This post highlights some of the patterns uncovered in the data - which are output area level migration flows for England and Wales (about 4 million individual flows). If you're interested in how I did this you can find out in <a href="http://undertheraedar.blogspot.co.uk/2014/10/flow-mapping-with-qgis.html" target="_blank">a previous post</a>. The first image is of the urban North West of England and for subsequent images I've zoomed to different parts of the country. I've kept it simple and only showed the flow lines, apart from in the North West where I've also added some place labels. It's all a bit experimental at this stage.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0N7z0KRcWWaiy1ueAUhZyeV-HOBE_QFJmDse5XuG-WTUlRddZH5pXzL-4YrC_tRuwp3Iuqfv77uT9CQJL9rHB5NU1DZEXlKHtZG2ktiaz4N0JYrHhD6NcVC5N5B9fC6PZWcih83iZTSM/s1600/nwmig2011.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj0N7z0KRcWWaiy1ueAUhZyeV-HOBE_QFJmDse5XuG-WTUlRddZH5pXzL-4YrC_tRuwp3Iuqfv77uT9CQJL9rHB5NU1DZEXlKHtZG2ktiaz4N0JYrHhD6NcVC5N5B9fC6PZWcih83iZTSM/s1600/nwmig2011.png" height="245" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">You can find a higher resolution image <a href="http://ajrae.staff.shef.ac.uk/img/nwmig2011.png" target="_blank">here</a></td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-5Fdki8Pa8zxeHbVltaO9Xr7CRaNY05oPimObI-zowyA2qGpo3J3jD-30sY8U7q-jj5TJMxyyizl3wvJxVFzq1RI0qWe4_O8QNDta88Jy3lLOlWxTlTLIXrqxk6P8neandpHyF0KufwE/s1600/nemig2011.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg-5Fdki8Pa8zxeHbVltaO9Xr7CRaNY05oPimObI-zowyA2qGpo3J3jD-30sY8U7q-jj5TJMxyyizl3wvJxVFzq1RI0qWe4_O8QNDta88Jy3lLOlWxTlTLIXrqxk6P8neandpHyF0KufwE/s1600/nemig2011.png" height="301" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The North East of England</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLZRxji4oTEb8s5U7ckrauakWFM6O8MSQvOAFPgOLxIRNXgilDRBJOZBysNX92KfJ7w-ETPn2QF2jvsrTiceOUeoNSoiyNBACTflT2lMUtFtS_rR717pqxGMdGAA3DdrswVqXwTpSmx2E/s1600/yomig2011.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiLZRxji4oTEb8s5U7ckrauakWFM6O8MSQvOAFPgOLxIRNXgilDRBJOZBysNX92KfJ7w-ETPn2QF2jvsrTiceOUeoNSoiyNBACTflT2lMUtFtS_rR717pqxGMdGAA3DdrswVqXwTpSmx2E/s1600/yomig2011.png" height="230" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">West, East and South Yorkshire</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPp8bn_FeLtbkHwY1FjyOf-XP-ftmpVgVxykBUXHja1ZhspmjPNWCqBBZg6lJhXkA_yHXoUZrUdQV32wYMFuQuoE4lN85gl9z2ywAGKUP6Uo_noF4zV1ifJOeC4qL1XfD_TTB6sndv3R4/s1600/nlon_beyond.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhPp8bn_FeLtbkHwY1FjyOf-XP-ftmpVgVxykBUXHja1ZhspmjPNWCqBBZg6lJhXkA_yHXoUZrUdQV32wYMFuQuoE4lN85gl9z2ywAGKUP6Uo_noF4zV1ifJOeC4qL1XfD_TTB6sndv3R4/s1600/nlon_beyond.png" height="227" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">I think some places are missing (working on it)</td></tr>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwVzR33ARBfEWJdRHRu-3k-ROuY1gZ4u4a3Cyq76h_Oo8LfJ7T75p6vRKV0fXbK0293wD7jHyn-i3cdrX3UMfXOo6d1QZc4BhsDgJ7yetQYiCoRmnbr6jvJifFFONkX3_xJJNdiNn1qrk/s1600/swmig2011.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwVzR33ARBfEWJdRHRu-3k-ROuY1gZ4u4a3Cyq76h_Oo8LfJ7T75p6vRKV0fXbK0293wD7jHyn-i3cdrX3UMfXOo6d1QZc4BhsDgJ7yetQYiCoRmnbr6jvJifFFONkX3_xJJNdiNn1qrk/s1600/swmig2011.png" height="251" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">I've adjusted the brightness a little to make this clearer</td></tr>
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What does all this show? It shows what many people may already know or expect but basically it illustrates the extent of residential mobility patterns in some of England's major urban areas - plus a bit more in the South West example above. There's a lot more that could be said about this but for now I'll leave it at that. I'm sorry if your town or city isn't on the map! Maybe next time...</div>
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<span style="font-size: x-small;"><b>Notes:</b> I've filtered the data so in certain cases some places are not shown (e.g. in the North West image places in North Wales are not visible). Also, I've only shown flows of a certain volume in order to filter out the noise. </span></div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-39723952792137591372014-12-23T20:23:00.000+00:002014-12-27T13:24:33.684+00:00Simple Animations with QGIS - A Long Tutorial<div style="text-align: justify;">
This rather long post explains how you can make images and animations like the ones below using only open source software (mostly <a href="http://www.qgis.org/en/site/" target="_blank">QGIS</a>) and open data. I've just used flights from Hartsfield-Jackson International Airport in Atlanta because it's the busiest airport in the world and serves a wide variety of destinations. The methods are relatively straightforward but it does take time to get your head around if you're new to the software and the data. If you're already a competent QGIS user it should be pretty easy. Once you've got the method nailed down you can apply it to all kinds of different scenarios and datasets. First of all, though, here's a static image of outbound flights from ATL projected onto a globe.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhIKBUExt46TzbWc43LrNAOoPwDJARzlHtG7xZnKydtmzoUezMnUQsJnUmphQihFCY818Ip2b-vLe9YqWcTJ-GvX2ImqrzgDeH3eXikHpZqX8ahLeASBFJBUOaTq69_750Sp37Ftm_G2w0/s1600/atl_out_example_crop.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhIKBUExt46TzbWc43LrNAOoPwDJARzlHtG7xZnKydtmzoUezMnUQsJnUmphQihFCY818Ip2b-vLe9YqWcTJ-GvX2ImqrzgDeH3eXikHpZqX8ahLeASBFJBUOaTq69_750Sp37Ftm_G2w0/s1600/atl_out_example_crop.png" height="320" width="284" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Flight destinations from Atlanta (<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhIKBUExt46TzbWc43LrNAOoPwDJARzlHtG7xZnKydtmzoUezMnUQsJnUmphQihFCY818Ip2b-vLe9YqWcTJ-GvX2ImqrzgDeH3eXikHpZqX8ahLeASBFJBUOaTq69_750Sp37Ftm_G2w0/s1600/atl_out_example_crop.png" target="_blank">full size</a>)</td></tr>
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The first thing you'll need to do is get some data. In this example I've taken some general <a href="http://www.naturalearthdata.com/downloads/50m-cultural-vectors/" target="_blank">country boundaries</a> from Natural Earth and for the flights data I've used the <a href="http://openflights.org/data.html" target="_blank">OpenFlights dataset</a>. I then created an azimuthal orthographic projection centred on Hartsfield-Jackson International Airport in Atlanta. Hamish Campbell already wrote an <a href="http://polemic.nz/2014/11/21/nz-azimuth-orthographic/" target="_blank">excellent tutorial</a> on how to do this in QGIS, so just follow that if you want to use a projection that makes your country layer appear as if it were on a globe. The only extra tips you'll perhaps need to replicate Hamish's method are as follows. To get the lat/long of a place you want to centre your projection on, just search for it on Google Maps and then look in the address bar for the coordinates. The python script on Hamish's page just needs to be copied and pasted into a text document, saved with a .py extension and then placed in the correct folder on your computer (on a PC with QGIS 2.4 it would be something like this: C:\Program Files\QGIS Chugiak\bin). Also, when you clip the layer to a global projection, QGIS will create a clip circle and a new clipped layer. These may not appear at all or if they do they'll maybe be very blocky. If so, go to the properties for the layer in QGIS and on the Rendering tab just untick 'Simplify Geometries'. I normally save new copies of these layers using Save As... from each layer.</div>
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjLuWvcJz0MyqBSyJ9P_cpa7NsNTjJIKwCZVUg3q8ex3gJSfFNFdlieeUFaPmuwJn8PxXAOLm7sSMA6-buRXAMxJx39polfojJQhDpGEDexe4-MWUOpv1gPOD4WVZojcDIlYEb24IggW7s/s1600/atl_out_fast.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjLuWvcJz0MyqBSyJ9P_cpa7NsNTjJIKwCZVUg3q8ex3gJSfFNFdlieeUFaPmuwJn8PxXAOLm7sSMA6-buRXAMxJx39polfojJQhDpGEDexe4-MWUOpv1gPOD4WVZojcDIlYEb24IggW7s/s1600/atl_out_fast.gif" height="292" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A faster animated version of ATL outbound flights (<a href="http://ajrae.staff.shef.ac.uk/img/atl_out_fast.gif" target="_blank">big</a>)</td></tr>
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That should be your global projection sorted. You can then apply it via the Project menu in QGIS and then Project Properties... CRS and then 'Project on the fly' as in the tutorial. To achieve some of the visual effects above, I just duplicated the clipped circle layer (you'll have to Save As... from the temp clipped layer to do this) and applied an inverted polygon style and a shapeburst fill with a blue to black gradient (Nyall Dawson did <a href="http://nyalldawson.net/2014/06/shapeburst-fill-styles-in-qgis-2-4/" target="_blank">a great blog post</a> on this, which you might find useful). I also did a similar thing with the land layer, just to make some of the smaller islands stand out. You'll also need to make the outline colour the same as the fill colour in the circle to avoid a line appearing through your earth.<br />
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<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEja4Dbqfgm3XFmZMINvIx7b6rXPb8uMAfbFiIyHdNhY2ZP3LXQU4KLtBD_7YT5Fesxn1-QV25iHgMg04F2Wm3iYB92LVuGIZU8Qm0ikPf9CH-QmQjyHCso7Bhk9nDj6fd-iwnIcaT67nGU/s1600/atl_out_slow_pause.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEja4Dbqfgm3XFmZMINvIx7b6rXPb8uMAfbFiIyHdNhY2ZP3LXQU4KLtBD_7YT5Fesxn1-QV25iHgMg04F2Wm3iYB92LVuGIZU8Qm0ikPf9CH-QmQjyHCso7Bhk9nDj6fd-iwnIcaT67nGU/s1600/atl_out_slow_pause.gif" height="292" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A very slow version, with a pause at the end (<a href="http://ajrae.staff.shef.ac.uk/img/atl_out_slow_pause.gif" target="_blank">big</a>)</td><td class="tr-caption" style="text-align: center;"><br /></td></tr>
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So far, so good. But what about the flight paths and animated dots? Well, to create the lines you can follow my blog post on <a href="http://undertheraedar.blogspot.co.uk/2014/10/flow-mapping-with-qgis.html" target="_blank">flow mapping in QGIS</a> and use the sample dataset I posted there. You'll need to calculate two new columns for this shapefile (see below) and use the MMQGIS plugin for QGIS (installed, as ever, via the Plugins menu). If you just add this file to your global azimuthal orthographic projection there will be so many lines and it may take a long time to display so there are a few intermediate steps I'd recommend... </div>
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<b>1</b>. Open the new global flights dataset in a blank QGIS project using the default projection and then remove duplicate lines using Modify, Delete Duplicate Geometries in the MMQGIS plugin. Many routes (e.g. JFK-LHR) are served by multiple airlines and I wanted to only show origins and destinations. This also makes the file much smaller. <b>2</b>. Although the flight connections would appear as straight lines on our global projection, I like them to look a little curved; partly for effect and partly to bring out the curvature of the earth but also because flight paths are not straight lines in reality. So, once I've removed duplicates I then 'densify' the lines in QGIS by adding in 50 intermediate vertices - done via Vector, Geometry Tools, Densify polygons in QGIS. <b>3</b>. I then added this new flights layer to my ATL-based global projection and I clipped the layer using the Hamish Campbell method, and saving the resulting layer as a new shapefile. You should now have a globe centred on the location of your choice, plus some nice curved airline flight paths.</div>
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<tr><td class="tr-caption" style="text-align: center;">Same as above, but with labels and pause at end (<a href="http://ajrae.staff.shef.ac.uk/img/atl_out_slow_labels.gif" target="_blank">big</a>)</td></tr>
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For the next stage, the way I did it was to open the dbf part of the new flight paths shapefile in Excel and then calculate an 'offset' lat and long column which I could use to animate the dots. You just need to read the Animate Columns part of Michael Minn's <a href="http://michaelminn.com/linux/mmqgis/" target="_blank">MMQGIS page</a> to understand this. Once you've calculated the new lat/long offset columns you can save the csv. Once you've done this, import the csv into QGIS using the Add Delimited Text Layer (comma icon), using the airport origin lat/long as the x,y coordinates in the import dialogue. Filter the new layer so it only shows ATL origins and you'll just see one dot for ATL but actually there are many dots in the same location as they all have the same origin lat/long. Save the filtered layer as a new shapefile and then run the Animate Columns tool in MMQGIS using the appropriate fields and the number of animation frames you want (50 works well with this example). An important point here is that you need to make sure your QGIS window is quite small as the extracted image frames will be the same size as your QGIS map frame and if it's too big it will make a massive GIF.<br />
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You now have all you need to create an animation. There are many ways to create an animated GIF, but using GIMP is very simple. You can download this free, open source image manipulation programme in a few minutes. You then just need to go to File, Open as Layers and then select all the frames you just created in QGIS and GIMP will add them to the project and they'll appear in the Layers pane. You don't need to reorder them as they are numbered correctly from the MMQGIS export. From here you can go to File, Export and then select the GIF file format and use the animation options here. Try 50 milliseconds between frames as with 50 frames this will create a nice short 2.5 second animation that isn't too slow. You should use Filters, Animation, Optimize for GIF and then export from that window if you want a much smaller file size. I created another one of these visuals, centred on LHR and showing flows from JFK, LHR and PEK.<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizE8ML39ZycxNq_JYvt_3uAxnONLwGAFPq2fVHTNJSWO9K8TYdDCsNwe-EC5t-2UTzP46x8FIKlTWLujpkdbQyCermw5exSc3W1s68I0UaBVKurSU9qYQ3EjcajJskiAk-vrakBtdiUMQ/s1600/jfk_lhr_pek.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEizE8ML39ZycxNq_JYvt_3uAxnONLwGAFPq2fVHTNJSWO9K8TYdDCsNwe-EC5t-2UTzP46x8FIKlTWLujpkdbQyCermw5exSc3W1s68I0UaBVKurSU9qYQ3EjcajJskiAk-vrakBtdiUMQ/s1600/jfk_lhr_pek.gif" height="320" width="317" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Same techniques, different data (and also a bit crazy)</td></tr>
</tbody></table>
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That's quite a lot of information and quite a few steps but if you try this and still can't make it work feel free to get in touch via <a href="https://twitter.com/undertheraedar" target="_blank">twitter</a> or <a href="https://www.shef.ac.uk/trp/staff/alasdair_rae" target="_blank">e-mail</a>. Why would you want to do this? I'll leave that up to anyone who wants to try it but displaying movements of people and goods is relevant across a number of disciplines so hopefully some will find this useful.<br />
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<br />
<span style="font-size: x-small;"><i><b>Other tips and information:</b></i> depending upon which location you're choosing, some of your lines or dots might be going the wrong way round the earth but you can fix this with a bit of simple maths in the offset calculation. In GIMP, you can add a different frame duration by adding a number and then ms to the layer info - <a href="http://www.gimp.org/tutorials/Simple_Animations/flower-anim.png" target="_blank">e.g. 1000ms</a> - so that it creates a pause effect, as in the examples above. I created an ATL point and a destination airports points layer from the imported csv so that I could manually create a couple of extra frames to add in to the end of my animation. One to show destinatinon airport names and the other just to label ATL. For the glow effect in the flow lines in the static image I used the Feature Blend 'addition' option in layer properties in QGIS. </span><br />
<span style="font-size: x-small;"><br /></span>
<span style="font-size: x-small;"><i><b>Acknowledgements:</b></i> As ever, I've borrowed ideas and techniques from other QGIS users, including <a href="https://twitter.com/polemic" target="_blank">Hamish Campbell</a>, <a href="http://nyalldawson.net/" target="_blank">Nyall Dawson</a>, <a href="http://nathanw.net/" target="_blank">Nathan Woodrow</a>. I decided to have a look at this after an e-mail exchange with <a href="http://www.geog.ucsb.edu/~tobler/" target="_blank">Waldo Tobler</a> about migration data. Thanks of course to the excellent OpenFlights team who make their data available under an <a href="http://opendatacommons.org/licenses/odbl/1.0/" target="_blank">Open Database Licence</a>.</span></div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-36471031795112682672014-12-17T21:32:00.001+00:002014-12-17T21:39:33.254+00:00The Era of Radical Concrete meets Twitter<div style="text-align: justify;">
Back in 2008, when I moved into my office at the University of Sheffield, there were three mashed up boxes sitting under the desk. My curiosity got the better of me and I spent the next few hours looking through thousands of slides in hanging folders. This turned out to be the image archive of <a href="https://www.flickr.com/people/jrjamesarchive" target="_blank">Jimmy James</a>, the first Professor of Planning in our <a href="http://www.sheffield.ac.uk/trp" target="_blank">Department</a> and former Chief Planner in England.<br />
<br />
In the summer of 2013, after securing funding from the University of Sheffield <a href="https://www.sheffield.ac.uk/alumni/support/fund" target="_blank">Alumni Fund</a>, I was able to hire Joe Carr and Philip Brown (recent graduates) to digitise the entire collection and upload it to our dedicated <a href="https://www.flickr.com/photos/jrjamesarchive/" target="_blank">JR James Archive Flickr site</a>. After more than 2 million views and a year online, the BBC magazine did a piece on the archive, called '<a href="http://www.bbc.co.uk/news/magazine-29082338" target="_blank">The era of radical concrete</a>' which created huge interest and led to a <a href="http://www.bbc.co.uk/news/magazine-29160925" target="_blank">follow up</a> from residents of the places featured in the images. But one image in particular puzzled us... It was simply labelled 'Housing Scotland' (see below for the original slide and the online scanned image) and we just couldn't fine an exact location for it, but we thought it was in the New Town of Cumbernauld, 15 miles or so from Glasgow.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtgY84eLyZRTU4nEPsL5X4ob5jNMHS6arowIuFppKbCqs0ES_8P5SKjKb_T_SbyvkgiI-5_N3-RJN473EgH8XbjYM6XM6C_YltVnkzuuDFzucccicHQcDLk3Rk6UbkDVUzZWAJ4t-GLz0/s1600/2014-12-17+13.20.50.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgtgY84eLyZRTU4nEPsL5X4ob5jNMHS6arowIuFppKbCqs0ES_8P5SKjKb_T_SbyvkgiI-5_N3-RJN473EgH8XbjYM6XM6C_YltVnkzuuDFzucccicHQcDLk3Rk6UbkDVUzZWAJ4t-GLz0/s1600/2014-12-17+13.20.50.png" height="320" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Note the 'MAY 67' date stamp</td></tr>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgz6Y8cTdMwTb-5mxdN75NQGeNWKhxfXQqTMGjAMsyRFiBT2H-2yRySeyOvkNkhciRGSulDbajJz_wTixRxHkpRaCdLxH-smxTrpTJotQzXXlJRHiLHR8mK56H2e5YVaRKRp7FXc5OhHhE/s1600/40d87d70e69c612a4c884c411348a8b2.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgz6Y8cTdMwTb-5mxdN75NQGeNWKhxfXQqTMGjAMsyRFiBT2H-2yRySeyOvkNkhciRGSulDbajJz_wTixRxHkpRaCdLxH-smxTrpTJotQzXXlJRHiLHR8mK56H2e5YVaRKRp7FXc5OhHhE/s1600/40d87d70e69c612a4c884c411348a8b2.jpg" height="211" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Are you the boy? Let us know!</td></tr>
</tbody></table>
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These images were used in teaching planners and urbanists for many years but some of them were not in the right place when we found the slides. We did well to track down the location of most images since between me, Philip and Joe we have a pretty good knowledge of most of the UK and we had thought the one above was of Cumbernauld, because that's where it appeared in the archive.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgNWZGMHP8tOATf482D6Q6-AvlIknpp0pgkC9lesY_y627VXqQyyEgCP4m0IQXTPG70eeeJ3o77QsMwKtUCf6yxHnQ4IF0e7KV9BqW7bkbb3iLnOlieMZWQJcbpNrgtxCvjRjn1_4Yc9j8/s1600/2014-12-17+11.59.44.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgNWZGMHP8tOATf482D6Q6-AvlIknpp0pgkC9lesY_y627VXqQyyEgCP4m0IQXTPG70eeeJ3o77QsMwKtUCf6yxHnQ4IF0e7KV9BqW7bkbb3iLnOlieMZWQJcbpNrgtxCvjRjn1_4Yc9j8/s1600/2014-12-17+11.59.44.jpg" height="240" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">The New Towns section of the original archive</td></tr>
</tbody></table>
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However, our interest was piqued when a commenter on Flickr said it definitely <i>wasn't</i> Cumbernauld. We tried a few times on Twitter, but to no avail. Even <a href="https://twitter.com/MunicipalDreams" target="_blank">@MunicipalDreams</a> couldn't help us. So, I tried one last time yesterday on Twitter and after 17 retweets we had suggestions that it was definitley NOT South Africa (!), but it might be 'somewhere in Cumbernauld', Falkirk, Dyce, Cwmbran, Killingworth, Peterlee or Saltcoats - among other places. I spent half the night looking round Craigavon, Crawley and Harlow, just to be sure. Nothing.<br />
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But this is where Twitter and the power of the crowd came to the fore. Actually, I should say this is when the determination of <a href="https://twitter.com/a_view_from" target="_blank">Michael Coates</a> came to the fore, because ... wait for it ... he found where the photo was taken. It is in fact Abbots View in Haddington, East Lothian - as you can see from the embedded Street View image below. I've shown the 2008 Street View here as it is a better match for location and light but this is definitely it. The perspective of the Google cameras is a little different from Jimmy's original lens but it's a clear match so I declare Michael Coates winner of the Internet today and forever, though the <a href="https://twitter.com/VisResCentreMMU" target="_blank">Visual Resources Centre at Manchester Metropolitan University</a> also deserve credit for joining the hunt.<br />
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<iframe frameborder="0" height="450" src="https://www.google.com/maps/embed?pb=!1m0!3m2!1sen!2suk!4v1418851227688!6m8!1m7!1seNKycwP8KmRp0gdswo6VIQ!2m2!1d55.96132565840225!2d-2.771321521655776!3f32.906551416565286!4f-9.760698914970902!5f0.7820865974627469" style="border: 0;" width="600"></iframe>
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<iframe frameborder="0" height="300" src="https://www.google.com/maps/embed?pb=!1m14!1m8!1m3!1d570697.750786308!2d-2.8216163773651037!3d56.03100056166388!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x4887a7b2b1866c33%3A0xcd6ed1b4fd5c9df!2sAbbots+View%2C+Haddington%2C+East+Lothian+EH41!5e0!3m2!1sen!2suk!4v1418851684930" style="border: 0;" width="400"></iframe>
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So, that's one mystery solved. But what about the other mystery? Who is the boy on the bike?<br />
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By my estimation he'd be about 50 now and if anyone tracks him down we'll <i>really</i> be impressed. In the meantime, if you haven't already looked at the <a href="https://www.flickr.com/photos/jrjamesarchive/" target="_blank">JR James Acrhive</a>, what are you waiting for?</div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-58806637383776313892014-12-11T09:36:00.001+00:002014-12-12T09:10:26.917+00:00Are you STILL here? Big Data's bad smell<div style="text-align: justify;">
<b>Rambling introduction</b></div>
<div style="text-align: justify;">
Big data, big data, big data, big data. Yes, we're all probably sick to death of hearing the term 'big data' now* and somewhere along the lines the meaning has disappeared and whatever feelings the term originally engendered have now morphed into angst, disillusionment, embarrassment and general scoffing. Maybe this is because the famous 3 Vs of big data (vanity, vanity and vanity**) have not actually produced many good examples that can help explain why and how big data is useful. Actually, this kind of thing is pretty common in tech, academic, business and all sorts of other fields. A new concept comes along, people start jumping on the bandwagon, people start jumping off the bandwagon, bandwagon crashes and burns, and everyone says 'I was never on the bandwagon and, anyway, it was going in the wrong direction'. Despite the sarcasm and general rambling nature of this opening paragraph, below the floppy disk I'm going to make the case for not abandoning 'big data' at all - even if we do decide to stop using the term. I may also throw in even more bad metaphors, analogies and bad writing.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="http://upload.wikimedia.org/wikipedia/commons/7/7e/Floppy_disk_300_dpi.jpg" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://upload.wikimedia.org/wikipedia/commons/7/7e/Floppy_disk_300_dpi.jpg" height="320" width="304" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">A 'big data' enabled storage device</td></tr>
</tbody></table>
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<b>Shark Jumping</b></div>
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In 2011 an <a href="http://www.dbms2.com/2011/09/11/big-data-has-jumped-the-shark/" target="_blank">article</a> appeared on dbms2.com saying 'big data' had 'jumped the shark' (see below, and <a href="https://www.google.co.uk/webhp?sourceid=chrome-instant&ion=1&espv=2&ie=UTF-8#q=define%3A%20jump%20the%20shark" target="_blank">here</a> for definition) and it makes for interesting reading because much of what it says is true. However, like most articles about big data, the core of the critique is not always directed towards the data or the analytical process but towards the hype. The comments section of this article is also very interesting because <a href="https://twitter.com/doug_laney" target="_blank">Doug Laney</a>, the originator of the much-cited 3v concept in big data, has a few things to say. Fast forward to September 2014 and <a href="http://www.techsling.com/2014/09/has-big-data-jumped-the-shark/" target="_blank">Techsling</a> ask whether big data has jumped the shark (conclusion seems to be yes, probably), whereas in 2013 <a href="http://www.wired.com/2013/08/dont-worry-big-data-hasnt-jumped-the-shark-yet/" target="_blank">Wired said not to worry</a> because big data had definitely not jumped the shark. However, my favourite article in this vein has to be the <a href="http://blog.syncsort.com/2012/04/has-big-data-nuked-the-fridge/" target="_blank">syncsort piece</a> entitled 'has big data nuked the fridge', which actually contains a lot of common sense from a real 'big data' person. As for me, I completely agree that the hype has gone far too far. However, let's keep working on large datasets with powerful machines and then let people know when we get some useful or interesting results. And let's not use big data as an excuse for clever, anti-social people to avoid speaking to real people.</div>
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="http://www.michaelbransonsmith.net/blog/wp-content/uploads/2012/06/fonzie-doesnt-make-it.gif" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://www.michaelbransonsmith.net/blog/wp-content/uploads/2012/06/fonzie-doesnt-make-it.gif" height="240" width="320" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">Big data didn't make it</td></tr>
</tbody></table>
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<b><br /></b>
<b>Voices of reason</b></div>
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When you are immersed in hype, it's very important to find some voices of reason. Two prominent voices that I like the sound of are Rob Kitchin and David Lazer. <a href="https://www.maynoothuniversity.ie/people/rob-kitchin" target="_blank">Rob Kitchin</a> is a professor at Maynooth University in Ireland and has written extensively on the need to approach big data sensibly and with a healthy degree of critique; most notably in his 2014 book <a href="http://www.uk.sagepub.com/books/Book242780?subject=F00&fs=1" target="_blank">The Data Revolution</a>. My personal favourite is his piece from June 2014 entitled '<a href="http://bds.sagepub.com/content/1/1/2053951714528481.full" target="_blank">Big Data, new epistemologies and paradigm shifts</a>' where he explores Anderson's '<a href="http://archive.wired.com/science/discoveries/magazine/16-07/pb_theory" target="_blank">end of theory</a>' piece and argues both that big data is disruptive but also that there is 'an urgent need for wider critical reflection'. Rob's stance is particularly interesting from a social science perspective but actually I find his conclusions resonate much more widely.<br />
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My other voice of reason in big data is <a href="http://www.davidlazer.com/infopage" target="_blank">David Lazer</a>, professor in Political Science <i>and </i>Computer and Information Science at Northeastern University and Visiting Scholar at the Kennedy School at Harvard, who wrote a great piece with colleagues on '<a href="http://www.sciencemag.org/content/343/6176/1203" target="_blank">The Parable of Google Flu: Traps in Big Data Analysis</a>' for Science in March 2014. Most people with an interest in big data probably know the story of Google Flu Trends because it made headlines for the wrong reasons in February 2013. Lazer et al. use this story to bring some reason to the big data debate and critique 'big data hubris'. Interestingly, they also talk about the need to incorporate 'small data':<br />
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"However, traditional “small data” often offer information that is not contained (or containable) in big data, and the very factors that have enabled big data are enabling more traditional data collection."<br />
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The conclusion of the Lazer et al. piece is not that we should abandon big data but rather that we need to understand what the recent data revolution means and then use innovative analytics to move towards a clearer understanding of our world.<br />
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<b>Big dog, small dog</b><br />
I have posted a photo below of a big dog and a small dog. They are both dogs. I can see why some people would get excited about big dogs. They can fetch bigger sticks. They can keep burglars at bay more easily and they are stronger, but they do take up more space. But the small dog has a really loud bark, can go places big dogs can't, knows just as much as the big dog and takes up less space in your house. They do require different approaches in relation to being looked after, but that's another issue altogether. Someone has even produced <a href="http://www.slate.com/blogs/wild_things/2014/11/12/big_data_dog_graph_popularity_of_dog_breeds_mapped_against_their_overall.html" target="_blank">a nice visual representation</a> of different kinds of big and small dogs.<br />
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<table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto; text-align: center;"><tbody>
<tr><td style="text-align: center;"><a href="http://mydogscool.com/wp-content/uploads/2011/10/LittleBigDog.png" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" src="http://mydogscool.com/wp-content/uploads/2011/10/LittleBigDog.png" /></a></td></tr>
<tr><td class="tr-caption" style="text-align: center;">They are both dogs</td></tr>
</tbody></table>
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<b>How to proceed</b><br />
Apologies for the big dog, small dog nonsense above but I've been sucked in to the big data debate over the past few years and it always makes me think of this. I don't even have a dog. But I do have lots of data and a fancy computer and this is what I have in common with lots of other people who are 'doing big data'. So, to conclude and by way of trying to say something useful about big data, here's a final few bullet points...<br />
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<ul>
<li>Let's accept that the hype around big data has gone too far and put that to one side. It's not novel or useful to say that 'big data has jumped the shark', 'big data is all hype', 'big data is dead' or other similar comments. The people who are working with big data and have a critical mind (Kitchin, Lazer et al.) already know all this.</li>
<li>Let's try to take a more nuanced approach to understanding what big data is***, what it is not and what it can and cannot do - along the lines of what Kitchin refers to as a 'contextually nuanced epistemology'.</li>
<li>We ought to understand that the reason 'big data' emerged was because of enhanced processing power in computers which arrived at roughly the same time as access to very large datasets. This created the ability to ask questions of data that we previously could not answer because of problems of 'small tools'. But it hasn't really led to many transformative developments that people know about. This needs to change.</li>
<li>Let's start with big questions rather than big data. A very obvious point but the criticism that big data so far has been a solution in search of a problem is in some cases justified. </li>
<li>Let's let the term 'big data' fade into the distance and keep working with large datasets and powerful computers on big societal challenges that we need to find the answers to (i.e. keep doing big data but stop calling it that).</li>
<li>Finally, let's keep in mind this statement form a <a href="http://www.ft.com/cms/s/2/21a6e7d8-b479-11e3-a09a-00144feabdc0.html" target="_blank">Financial Times Magazine piece</a> on big data from early 2014: "a theory-free analysis of mere correlations is inevitably fragile. If you have no idea what is behind a correlation, you have no idea what might cause that correlation to break down". </li>
</ul>
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<span style="font-size: x-small;">* or 1 3, 5, 7, 10 years ago depending upon how far ahead of <a href="http://blogs.gartner.com/svetlana-sicular/big-data-is-falling-into-the-trough-of-disillusionment/" target="_blank">the curve</a> you are.</span></div>
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<span style="font-size: x-small;">** I <a href="http://www.sas.com/en_us/insights/big-data/what-is-big-data.html" target="_blank">think</a> that's right...</span><br />
<span style="font-size: x-small;">*** data is, data are... I like is, even if some say it's wrong</span><br />
<span style="color: white; font-size: x-small;">This blog is written in a somewhat rambling, tongue-in-cheek style just to make a point</span></div>
Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.comtag:blogger.com,1999:blog-6894739087790608261.post-66117822742562064222014-12-03T11:28:00.000+00:002014-12-03T11:28:35.614+00:00WIMD 2014 Shapefiles and Maps<div style="text-align: justify;">
The Welsh Index of Multiple Deprivation 2014 was <a href="http://wales.gov.uk/statistics-and-research/welsh-index-multiple-deprivation/?lang=en#/statistics-and-research/welsh-index-multiple-deprivation/?lang=en" target="_blank">published on 26 November</a>, using more up to date and improved indicators. The Welsh Government have provided some nice <a href="http://wimd.wales.gov.uk/" target="_blank">interactive mapping</a>, but <a href="http://ukdataexplorer.com/wimd/" target="_blank">James Trimble's version</a> is I think even better. I've done basic interactive versions in the past, but today I just want to share the raw GIS data and a few maps, for anyone who is interested in either looking more closely at their area or doing a bit of spatial analysis themselves. First of all, here are a few basic WIMD maps, clipped to building outlines (click images to enlarge).</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheNxaGLMdy8Wk1qtvPxSuxMjCPzQfpM5WaLbBvnnb3OwvSoVLhOiHP6kUPGlRbKYsMEsgwga1pYGDvWEs4saUu_swvvWzSX8VknbgYssnyJ4cm07H-IhF70x30ChTkSF_3rw-NZRCEtP4/s1600/Bridgend.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheNxaGLMdy8Wk1qtvPxSuxMjCPzQfpM5WaLbBvnnb3OwvSoVLhOiHP6kUPGlRbKYsMEsgwga1pYGDvWEs4saUu_swvvWzSX8VknbgYssnyJ4cm07H-IhF70x30ChTkSF_3rw-NZRCEtP4/s1600/Bridgend.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6osP66aMEq2eDBrQu-eziJk5DINL8gQvGtmSkng1a5jQ_RC7dDAKoU210WpxKiOuumxuXbp8X2P8sq-EEDUQgpJWd_xQK-PKjaBzaJUJ48thHwZC347iKvqttb_458Bv9h1Y5U1M51m0/s1600/Cardiff.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj6osP66aMEq2eDBrQu-eziJk5DINL8gQvGtmSkng1a5jQ_RC7dDAKoU210WpxKiOuumxuXbp8X2P8sq-EEDUQgpJWd_xQK-PKjaBzaJUJ48thHwZC347iKvqttb_458Bv9h1Y5U1M51m0/s1600/Cardiff.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWbgQitbMQja96V7HvoJ1Mg2UYU8tjGxS24oWlL-ahqS6fvmSV5lKL4SMjlY46CIuSDfxRRemNdN5lIp8ShFmuYXPOREmJ7YAF9o-JAUOp49KB5SHWBxNiBQp7atdz1pEcATx58knuIoA/s1600/Flintshire.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgWbgQitbMQja96V7HvoJ1Mg2UYU8tjGxS24oWlL-ahqS6fvmSV5lKL4SMjlY46CIuSDfxRRemNdN5lIp8ShFmuYXPOREmJ7YAF9o-JAUOp49KB5SHWBxNiBQp7atdz1pEcATx58knuIoA/s1600/Flintshire.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsbWknvmUHuj5qYEz-B2SgcWxK9EX3eeAdFbggquh9e_G1nKtnIeB87eLeZpvob8EifDge_1mTIGFSX0Nm3BgakWUe4Jx08gsEzdV5gSBJNvwfaBAevXO4c2S_HZr0nHR3yyMW68NUD1Y/s1600/Newport.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjsbWknvmUHuj5qYEz-B2SgcWxK9EX3eeAdFbggquh9e_G1nKtnIeB87eLeZpvob8EifDge_1mTIGFSX0Nm3BgakWUe4Jx08gsEzdV5gSBJNvwfaBAevXO4c2S_HZr0nHR3yyMW68NUD1Y/s1600/Newport.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjj8Le-zw5foMO6Wd3Zeju1-JXqCUyZE6ozHTmwzu0i5U17cti25KcIyt2PS_7GXrlDa3dV7H-i5M3Gwy97yGsB3mqKBvDgICH6zXJ54aR7ZHeM2_zmsam9FhbaaznYLCOOZOLp-gp2iwI/s1600/Swansea.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjj8Le-zw5foMO6Wd3Zeju1-JXqCUyZE6ozHTmwzu0i5U17cti25KcIyt2PS_7GXrlDa3dV7H-i5M3Gwy97yGsB3mqKBvDgICH6zXJ54aR7ZHeM2_zmsam9FhbaaznYLCOOZOLp-gp2iwI/s1600/Swansea.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheChe8xBFv_r9T02iwcdd4Gpn7WFb3lWQzoBqBTplJctCbp6UfLZytLCPg6d4Jzt0Jfz0-KdtktwOanPx0w5zxba49Fd0HqYc3nitt0BLGHNqTVpV-leHcukRx-NtMXO3GZnxORatMoGQ/s1600/The+Vale+of+Glamorgan.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEheChe8xBFv_r9T02iwcdd4Gpn7WFb3lWQzoBqBTplJctCbp6UfLZytLCPg6d4Jzt0Jfz0-KdtktwOanPx0w5zxba49Fd0HqYc3nitt0BLGHNqTVpV-leHcukRx-NtMXO3GZnxORatMoGQ/s1600/The+Vale+of+Glamorgan.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhsSvbxapO5EQ44AMdcO0oYc3d0XPAYFDOypMYW8b2jF0s5htvCQ_qfjc17k7MbxqzGaty10oP3IYQDkUWT_GOuOctfvXoelbaiIwI39oPZwruHBl3Vt06Am3XF15Id_C-ImyLDpunAcrM/s1600/Wrexham.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhsSvbxapO5EQ44AMdcO0oYc3d0XPAYFDOypMYW8b2jF0s5htvCQ_qfjc17k7MbxqzGaty10oP3IYQDkUWT_GOuOctfvXoelbaiIwI39oPZwruHBl3Vt06Am3XF15Id_C-ImyLDpunAcrM/s1600/Wrexham.png" height="226" width="320" /></a></div>
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I made these in QGIS, using an automated atlas <a href="http://undertheraedar.blogspot.co.uk/2014/11/automatic-map-production-with-qgis.html" target="_blank">production technique I've described</a> on the blog before. If you are looking to produce some WIMD maps, you might want to try this method. I've also produced some WIMD 2014 maps in standard choropleth format, as you can see below. These are okay in areas which are densely populated but I find them more misleading for larger rural areas where there are not many people.</div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPM5LE8mhLxvsDOZmcJCN6UtLMr623wmLz-Z2B4BMkOf3ReSEMr17-ozAUiFwIASg5WSAosnbI_AucT9quBcaF0i11YjF7VR9hOe6PeVXB_jtZYVi4wVgU4KrHqKpzEdJaTKPeiRBSpvI/s1600/Caerphilly.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgPM5LE8mhLxvsDOZmcJCN6UtLMr623wmLz-Z2B4BMkOf3ReSEMr17-ozAUiFwIASg5WSAosnbI_AucT9quBcaF0i11YjF7VR9hOe6PeVXB_jtZYVi4wVgU4KrHqKpzEdJaTKPeiRBSpvI/s1600/Caerphilly.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxxxnKFsyzIM_sLmSPy-xEWeUHrtvQbWCma3gXU-cpvbehOYTUOa7cHqj328-6W9kEDG4c1fdB47WJ5WpJsS8QdXgvZIZ8du-bjkBS7_U-97pSzsmdDWp0kyCCUZQM7Cll0a89_afc2k8/s1600/Cardiff.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxxxnKFsyzIM_sLmSPy-xEWeUHrtvQbWCma3gXU-cpvbehOYTUOa7cHqj328-6W9kEDG4c1fdB47WJ5WpJsS8QdXgvZIZ8du-bjkBS7_U-97pSzsmdDWp0kyCCUZQM7Cll0a89_afc2k8/s1600/Cardiff.png" height="226" width="320" /></a></div>
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<a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgy5UNp9qkEf2tq6IL2SI57uHr5x_yqORqWmlX3aHe56hCx1C6ucFCuc66F5Ic4pmITOeJ-52YGkjmIgWSEXhmQxNdWbk4M5mWhyphenhyphentp7jJ-mRfgPZDFzZ9zxzwcwXFtUWp_SWWjWjIpMWv8/s1600/Swansea.png" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgy5UNp9qkEf2tq6IL2SI57uHr5x_yqORqWmlX3aHe56hCx1C6ucFCuc66F5Ic4pmITOeJ-52YGkjmIgWSEXhmQxNdWbk4M5mWhyphenhyphentp7jJ-mRfgPZDFzZ9zxzwcwXFtUWp_SWWjWjIpMWv8/s1600/Swansea.png" height="226" width="320" /></a></div>
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I know a lot of people across the public sector in particular will be looking closely at the data, so I thought it would be helpful to make the underlying shapefiles publicly available since the data are open. If you click on the link below you'll be taken to a download page via Google Drive. Any questions, then feel free to get in touch.</div>
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Download files: <a href="https://drive.google.com/file/d/0B0kRhiw4fD7uQlU4TUt5XzVxUmc/view?usp=sharing" target="_blank">WIMD 2014 Shapefiles - for LSOAs and LSOAs clipped to building outlines</a>.</div>
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Alasdair Raehttp://www.blogger.com/profile/03780864826347238304noreply@blogger.com