{"id":1369,"date":"2022-08-31T21:52:00","date_gmt":"2022-08-31T20:52:00","guid":{"rendered":"https:\/\/www.geonatives.org\/?p=1369"},"modified":"2022-09-11T17:35:02","modified_gmt":"2022-09-11T16:35:02","slug":"peoples-republic-perspective%ef%bf%bc","status":"publish","type":"post","link":"https:\/\/www.geonatives.org\/?p=1369","title":{"rendered":"People\u2019s Republic Perspective"},"content":{"rendered":"\n<p class=\"has-text-align-center\"><sub>(4 min read)<\/sub><\/p>\n\n\n\n<p>Have you ever visited China using <a rel=\"noreferrer noopener\" href=\"https:\/\/www.google.com.hk\/maps\" target=\"_blank\">Googles\u2019 map service<\/a> and asked yourself, why the road networks are not matching the aerial images? And maybe you have double-checked this oddity in <a rel=\"noreferrer noopener\" href=\"https:\/\/www.bing.com\/maps\/\" target=\"_blank\">Bing\u2019s map service<\/a> and realized the same issue? But have you checked it, for example, with <a rel=\"noreferrer noopener\" href=\"https:\/\/duckduckgo.com\/Map\" target=\"_blank\">Apple\u2019s map service<\/a> or the map services from the South Korean search engine <a rel=\"noreferrer noopener\" href=\"https:\/\/m.map.naver.com\" target=\"_blank\">Naver<\/a>, the Russian one from <a rel=\"noreferrer noopener\" href=\"https:\/\/yandex.com\/maps\/\" target=\"_blank\">Yandex<\/a> or even <a rel=\"noreferrer noopener\" href=\"https:\/\/map.baidu.com\/\" target=\"_blank\">Baidu\u2019s map service<\/a>? There, everything looks like normal. And did you have the opportunity to check Google\u2019s map service while you are in China and realized that now it fits there as well? What happened?<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-far-1024x576.jpg\" alt=\"\" class=\"wp-image-1385\" srcset=\"https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-far-1024x576.jpg 1024w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-far-300x169.jpg 300w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-far-768x432.jpg 768w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-far.jpg 1280w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption><em>Looking from above is telling only half of the truth (Tianjin, image by Andreas Richter)<\/em><\/figcaption><\/figure>\n\n\n\n<p>The explanation starts with two facts we already touched in our earlier posts:<\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>First: The Earth is bumpy and, additionally, makes it complicated for us humans to be simplified from its three-dimensional shape into two-dimensional visualizations. For that, so-called <a href=\"https:\/\/www.geonatives.org\/?p=206\">projections were invented to \u201cmap\u201d the world<\/a>. The most famous one is the Mercator projection using 60 cylinders to map the earth. It works quite well for everything close to the equator but everything further north and south gets increasingly distorted. But why should this deviation end at the &#8220;Great Wall&#8221;? Stay tuned!<\/li><\/ul>\n\n\n\n<ul class=\"wp-block-list\"><li>Second: For China, <a href=\"https:\/\/www.geonatives.org\/?p=1296\">geodata is strategic data<\/a>. In China, mapping is part of the development of the national economy and build-up of national defense (among other things). In our recent <a href=\"https:\/\/www.geonatives.org\/?p=1192\">expert interview with Li Qingjian<\/a> you can read more about the geodata sourcing based on the management of national policy qualification. Each mapping company needs a permission from the state to map in China and then the <a href=\"https:\/\/en.wikipedia.org\/wiki\/Restrictions_on_geographic_data_in_China\">map data has to stay in China<\/a>. Copying data is obviously the easiest way to get data to somewhere else and therefore China&#8217;s geodata gets some kind of a copy protection which is realized through coordinate obfuscation.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Security by Obscurity<\/h2>\n\n\n\n<p>China uses the <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Restrictions_on_geographic_data_in_China#GCJ-02\" target=\"_blank\">GCJ02<\/a> geodetic datum that is based on WGS84, which is used by GPS. GCJ02 is officially called \u201cTopographic map non-linear confidentiality algorithm\u201d and adds a distortion algorithm on top. But it does so not only by longitudinal and lateral offset, it does it randomly (different tessellation for each region) so that the offset is not the same for any two locations. In other words, the algorithm is messing up the 3d coordinate data compared to WGS84 coordinates. Due to the randomness of the distortion, no coordinate reference system definitions nor any transformations exist in the <a rel=\"noreferrer noopener\" href=\"https:\/\/epsg.org\/home.html\" target=\"_blank\">EPSG Registry<\/a> for GCJ02.<\/p>\n\n\n\n<p>To work with map data in China you have to get a license from Chinese State Bureau of Surveying and Mapping and purchase a shift correction algorithm. This shift correction box will decrypt the data and makes it \u201cusable\u201d e.g., to compare it with WGS84-based data. You ask yourself, why not using pure GPS coordinates such as OpenStreetMap does? The simple answer is: It&#8217;s illegal.<\/p>\n\n\n\n<p>If map providers show &#8220;roads matching with areal images&#8221;, you can expect that both, roads and images are wrong (read: at the wrong geolocation). The mismatch in Google\u2019s map service is because of the aerial images being still correctly referenced (in terms of WGS84).<\/p>\n\n\n\n<p>The mystical \u201cnon-linear confidentiality algorithm\u201d was leaked years ago and therefore some open-source implementation for correction exist. However, Baidu\u2019s map uses an additional geographic coordinate system called BD09 that adds additional distortion to the geodata for the sake of \u201c<a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Baidu_Maps#Coordinate_system\" target=\"_blank\">user\u2019s privacy<\/a>\u201d. And, of course, BD09 can&#8217;t be found in EPSG Registry either.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Getting the real China<\/h2>\n\n\n\n<p>If you wanted to create a road network without the user privacy correction, you could process correctly referenced aerial or satellite images and extract the road network using computer graphics approaches. <a href=\"https:\/\/www.geonatives.org\/?p=1218\">Seen from space, none of the borders count at all<\/a>! But, if you want to create lane-level detailed maps, it will get complicated. Mobile mapping is only allowed with permission and the data stays in the country with the encryption. High-resolution images necessitate satellites with costly cameras. Most high-resolution images are obtained by aerial surveys and again you will need permission and the data\u2026 you get it.<\/p>\n\n\n\n<p>But there is one scientific solution: You can at least improve the correctness of aerial images with the help of &#8220;landmarks&#8221;. The project <a rel=\"noreferrer noopener\" href=\"https:\/\/www.helmholtz.de\/en\/newsroom\/article\/the-revolution-on-our-roads\/\" target=\"_blank\">DriveMark<\/a> uses data from the radar satellite project <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/TanDEM-X\" target=\"_blank\">TanDEM-X<\/a> and adds sophisticated ionospheric and tropospheric correction <em>and<\/em> takes geodynamic effects (tides) into account. With this help, vertical objects like poles and pylons can be identified as retro reflectors with a very high absolute accuracy. These landmarks can be recovered in the aerial images. If multiple landmarks can be found in an aerial image, a correction can be applied and in China most modern roads are equipped with numerous pole-like infrastructure such as traffic signs, traffic lights and street lighting. The start-up company ternow.ai is utilizing this technology to <a rel=\"noreferrer noopener\" href=\"https:\/\/ternow.ai\/#product-section\" target=\"_blank\">create accurate lane-level detailed maps from aerial images<\/a>. With the described combination of data you could create a precise map of Chinese roads. However, high-resolution aerial images are expensive to obtain and it will cause other (legal) conflicts if you operate with such kind of data in China.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p>Geodata rules the world. And if you want to make sure that nobody is surveying your property unbeknown by yourself, you set up your own perspective and let others use your understanding of reality.<\/p>\n\n\n\n<p><strong>Addendum<\/strong><\/p>\n\n\n\n<p>The <a rel=\"noreferrer noopener\" href=\"https:\/\/www.youtube.com\/watch?v=L9Di-UVC-_4\" target=\"_blank\">video<\/a> from \u201cHalf as Interesting\u201d is quite a good summary of the case.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-near-1024x576.jpg\" alt=\"\" class=\"wp-image-1383\" srcset=\"https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-near-1024x576.jpg 1024w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-near-300x169.jpg 300w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-near-768x432.jpg 768w, https:\/\/www.geonatives.org\/wp-content\/uploads\/2022\/08\/China-near.jpg 1280w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption><em>Sometimes, location really matters (Anting, image by Marius Dupuis)<\/em><\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>Have you ever visited China using a map service and asked yourself, why the road networks are not matching the aerial images? And when checking in China, everything fits?<\/p>\n","protected":false},"author":2,"featured_media":1386,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7,14,1],"tags":[36,68,43,35,39],"class_list":["post-1369","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-processing","category-oddities","category-uncategorized","tag-absolute","tag-china","tag-maps","tag-relative","tag-trueness"],"_links":{"self":[{"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/posts\/1369","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1369"}],"version-history":[{"count":11,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/posts\/1369\/revisions"}],"predecessor-version":[{"id":1397,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/posts\/1369\/revisions\/1397"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=\/wp\/v2\/media\/1386"}],"wp:attachment":[{"href":"https:\/\/www.geonatives.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1369"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1369"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.geonatives.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1369"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}