{"id":105,"date":"2020-07-28T22:21:33","date_gmt":"2020-07-28T14:21:33","guid":{"rendered":"http:\/\/new.meicmodel.org\/?page_id=105"},"modified":"2020-07-31T10:43:22","modified_gmt":"2020-07-31T02:43:22","slug":"satellite-data","status":"publish","type":"page","link":"http:\/\/meic-dev.makenv.com\/?page_id=105&lang=en","title":{"rendered":"Satellite-Derived PM2.5 Database"},"content":{"rendered":"\n<div class=\"wp-block-cover\" style=\"background-image:url(http:\/\/new.meicmodel.org\/wp-content\/uploads\/2020\/07\/back.png);background-position:100% 50%;min-height:182px;aspect-ratio:unset;\"><div class=\"wp-block-cover__inner-container is-layout-flow wp-block-cover-is-layout-flow\">\n<p class=\"has-text-align-left has-large-font-size wp-block-paragraph\">TAP dataset<\/p>\n<\/div><\/div>\n\n\n\n<hr style=\"height:3px;background-color:black;\">\n<h3>Data description &gt;<\/h3>\n<hr style=\"height:1px;background-color:#aaa;\">\n\n\n\n<p class=\"wp-block-paragraph\">This PM<sub>2.5<\/sub> concentration prediction dataset fused the satellite aerosol optical depth (AOD) retrieval, chemical transport model (CMAQ) simulation, and ground PM<sub>2.5<\/sub> measurement through a machine learning algorithm. By filling the missing satellite data due to cloud cover and high surface reflectance, our method provides spatiotemporally continuous daily PM<sub>2.5<\/sub> and PM<sub>2.5<\/sub> composition maps covering China.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The gridded daily average PM<sub>2.5<\/sub> concentration data are at 0.1\u00b0 resolution, covering 73.25\u00b0-135.25\u00b0E and 18.15\u00b0-53.75\u00b0N according to the centroid of grid. The current dataset covers China during February 25, 2000 &#8211; December 31, 2019. Predictions after 2019 will be rolling update.<\/p>\n\n\n\n<hr style=\"height:3px;background-color:black;\">\n<h3>Data version &gt;<\/h3>\n<hr style=\"height:1px;background-color:#aaa;\">\n\n\n\n<ul class=\"wp-block-list\"><li>The predictions during 2000-2019 are from the fixed model trained by data during 2013-2019.<\/li><li>The predictions after 2019 are from a rolling update model trained by data during a one-year time window that includes the prediction time period. This model will provide near real-time predictions.<\/li><\/ul>\n\n\n\n<hr style=\"height:3px;background-color:black;\">\n<h3>Citation &gt;<\/h3>\n<hr style=\"height:1px;background-color:#aaa;\">\n\n\n\n<p class=\"wp-block-paragraph\">Xiao, Q., Chang, H. H., Geng, G. &amp; Liu, Y. An Ensemble Machine-Learning Model To Predict Historical PM<sub>2.5<\/sub> Concentrations in China from Satellite Data. <em>Environmental Science &amp; Technology<\/em> <strong>52<\/strong>, 13260-13269, doi:10.1021\/acs.est.8b02917 (2018)<\/p>\n\n\n\n<hr style=\"height:3px;background-color:black;\">\n<h3>Download &gt;<\/h3>\n<hr style=\"height:1px;background-color:#aaa;\">\n\n\n\n<p class=\"wp-block-paragraph\">We provide <a href=\"http:\/\/new.meicmodel.org\/?page_id=51\">customized satellite-derived PM<sub>2.5<\/sub> and PM<sub>2.5<\/sub> composition concentration data<\/a> with the user-specific temporal period and spatial coverage.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Data description &gt; This PM2.5 concentration predicti&hellip;<\/p>\n<p class=\"more-link\"><a href=\"http:\/\/meic-dev.makenv.com\/?page_id=105&#038;lang=en\" class=\"themebutton2\">Read More<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-105","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/pages\/105","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=105"}],"version-history":[{"count":8,"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/pages\/105\/revisions"}],"predecessor-version":[{"id":321,"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=\/wp\/v2\/pages\/105\/revisions\/321"}],"wp:attachment":[{"href":"http:\/\/meic-dev.makenv.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=105"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}