{"id":551,"date":"2025-07-12T19:27:01","date_gmt":"2025-07-12T19:27:01","guid":{"rendered":"https:\/\/ccds.ai\/?p=551"},"modified":"2025-08-10T18:15:12","modified_gmt":"2025-08-10T18:15:12","slug":"understanding-the-urban-environment-from-satellite-data","status":"publish","type":"post","link":"https:\/\/ccds.ai\/?p=551","title":{"rendered":"Understanding the Urban Environment from Satellite Data"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-75j9b-5c02678ae204902189e7c2f7e5c02090 main_color avia-section-default avia-no-border-styling  avia-builder-el-0  avia-builder-el-no-sibling  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><main  role=\"main\" itemprop=\"mainContentOfPage\"  class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-551'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-md4uqnao-df252af92216a112144f7a7a5bc5aeb5\">\n.avia-image-container.av-md4uqnao-df252af92216a112144f7a7a5bc5aeb5 img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-md4uqnao-df252af92216a112144f7a7a5bc5aeb5 .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-md4uqnao-df252af92216a112144f7a7a5bc5aeb5 av-styling- avia-align-center  avia-builder-el-1  el_before_av_textblock  avia-builder-el-first '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img fetchpriority=\"high\" fetchpriority=\"high\" decoding=\"async\" class='wp-image-601 avia-img-lazy-loading-not-601 avia_image ' src=\"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability.png\" alt='' title='mdpi_sustainability'  height=\"769\" width=\"1063\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability.png 1063w, https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability-300x217.png 300w, https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability-1030x745.png 1030w, https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability-768x556.png 768w, https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability-705x510.png 705w\" sizes=\"(max-width: 1063px) 100vw, 1063px\" \/><\/div><\/div><\/div>\n<section  class='av_textblock_section av-md0mzsvd-3e86b993b7971c3ec3228637f38719e7'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p>This project is a collaboration between CCDS and the Center for Spatial Information Science, The University of Tokyo, Japan. Based on easily accessible data from Google Earth, this work develops and proposes a new urban environment classification method focusing on formality and informality. The method developed in this work divides the urban environment into 16 categories under four classes. Then it is used to draw the urban environment classes maps of the following emerging cities: Nairobi in Kenya, Mumbai in India, Guangzhou in China, Jakarta in Indonesia, Cairo in Egypt, and Lima in Chile. The characteristics of the different urban environments and the differences between the same class in different cities are investigated. The paper also demonstrate the agility of the proposed method by showing how this classification method can be easily augmented with other data such as population per square kilometer to aid the decision-making process.<\/p>\n<\/div><\/section>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":601,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[90],"tags":[],"class_list":["post-551","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data_sci_projects"],"acf":[],"jetpack_featured_media_url":"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/mdpi_sustainability.png","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/551","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=551"}],"version-history":[{"count":5,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/551\/revisions"}],"predecessor-version":[{"id":607,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/551\/revisions\/607"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/media\/601"}],"wp:attachment":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=551"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=551"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=551"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}