{"id":1586,"date":"2024-11-04T00:01:57","date_gmt":"2024-11-04T05:01:57","guid":{"rendered":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/?page_id=1586"},"modified":"2025-11-09T20:52:22","modified_gmt":"2025-11-10T01:52:22","slug":"data","status":"publish","type":"page","link":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/","title":{"rendered":"Data"},"content":{"rendered":"\n<p>Below are the datasets our lab uses as well as curated.&nbsp; The paper citations for the datasets have been added as well.<\/p>\n\n\n\n<hr>\n<p>&nbsp;<\/p>\n\n\n\n<h2>TROPOMI-derived ground ozone in California<\/h2>\n<p>Using the TROPOMI satellite data and the HRRR meteorological feild, the daily-level ground ozone concentrations were estimated using random forest model. TROPOMI data improved the estimate of extreme values when compared to a similar model without it. Our study demonstrates the feasibility and value of using TROPOMI data in the spatiotemporal characterization of ground-level ozone concentration.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg\" alt=\"\" height=\"290\" aria-describedby=\"cn0025\"><\/p>\n<p>Spatial Resolution: 10 km<\/p>\n<p>Temporal Resolution: daily<\/p>\n<p>Temporal Coverage: May 2018 &#8211; April 2019<\/p>\n<p>The estimated ozone season, non-ozone season average ozone concentrations and the model was publicly available at: &nbsp;<a href=\"https:\/\/zenodo.org\/records\/14498553\">https:\/\/zenodo.org\/records\/14498553<\/a><\/p>\n<p><strong>Reference:&nbsp;<\/strong>Wang, W., Liu, X., Bi, J., &amp; Liu, Y. (2022). A machine learning model to estimate ground-level ozone concentrations in California using TROPOMI data and high-resolution meteorology. <i>Environment International<\/i>, <i>158<\/i>, 106917.<a href=\"https:\/\/doi.org\/10.1016\/j.envint.2021.106917\"><span style=\"color: #0000ff\"> [link]<\/span><\/a><\/p>\n\n\n\n<hr>\n<p>&nbsp;<\/p>\n\n\n\n<h1>CONUS smoke PM<sub>2.5<\/sub> estimation<\/h1>\n<p>We estimated daily air pollution levels (PM<sub>2.5<\/sub>) across the United States by combining data from government monitors, low-cost sensors, and computer models. We used additional information from satellites, weather data, and smoke maps to improve coverage and accuracy. To separate smoke from wildfire events from other pollution sources, we built models that compared air quality in smoky and non-smoky areas. This approach allowed us to estimate how much of the air pollution came specifically from wildfire smoke each day.<\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1700 aligncenter\" src=\"http:\/\/scholarblogs.emory.edu\/remote-sensing-group\/files\/2025\/11\/es3c05143_0004.jpg\" alt=\"\" width=\"610\" height=\"372\" \/><\/p>\n<p><strong>Reference: <\/strong>Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States<br \/>Danlu Zhang, Wenhao Wang, Yuzhi Xi, Jianzhao Bi, Yun Hang, Qingyang Zhu, Qiang Pu, Howard Chang, and Yang Liu<br \/>Environmental Science &amp; Technology 2023 57 (48), 19990-19998, DOI: 10.1021\/acs.est.3c05143<\/p>\n<h3>The original data is available at 1km resolution. Different levels of this dataset were available, as outlined below:<\/h3>\n<h4>1. ZIP daily level<\/h4>\n<p>For the ZIP-level daily data, the 1 km total and nonfire PM<sub>2.5<\/sub> estimates were aggregated to ESRI ZIP Code boundaries using the arithmetic mean for all grid points within each ZIP. Daily smoke PM<sub>2.5<\/sub> at the ZIP level was then computed as the difference between the aggregated total and nonfire PM<sub>2.5<\/sub> estimates.\u00a0<\/p>\n<p>Spatial Resolution:\u00a0 ESRI ZIP code<\/p>\n<p>Temporal Resolution: daily<\/p>\n<p>Temporal Coverage: Jan 2007 &#8211; Dec 2018<\/p>\n<p>The data is available at:\u00a0<a href=\"https:\/\/zenodo.org\/records\/17289804\">https:\/\/zenodo.org\/records\/17289804<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Below are the datasets our lab uses as well as curated.&nbsp; The paper citations for the datasets have been added as well. &nbsp; TROPOMI-derived ground ozone in California Using the TROPOMI satellite data and the HRRR meteorological feild, the daily-level ground ozone concentrations were estimated using random forest model. TROPOMI data improved the estimate of [&hellip;]<\/p>\n","protected":false},"author":8813,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"ngg_post_thumbnail":0,"footnotes":""},"class_list":["post-1586","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Data - Emory Environmental Remote Sensing Group<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data - Emory Environmental Remote Sensing Group\" \/>\n<meta property=\"og:description\" content=\"Below are the datasets our lab uses as well as curated.&nbsp; The paper citations for the datasets have been added as well. &nbsp; TROPOMI-derived ground ozone in California Using the TROPOMI satellite data and the HRRR meteorological feild, the daily-level ground ozone concentrations were estimated using random forest model. TROPOMI data improved the estimate of [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/\" \/>\n<meta property=\"og:site_name\" content=\"Emory Environmental Remote Sensing Group\" \/>\n<meta property=\"article:modified_time\" content=\"2025-11-10T01:52:22+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/\",\"url\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/\",\"name\":\"Data - Emory Environmental Remote Sensing Group\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/#primaryimage\"},\"image\":{\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/ars.els-cdn.com\\\/content\\\/image\\\/1-s2.0-S0160412021005420-gr5.jpg\",\"datePublished\":\"2024-11-04T05:01:57+00:00\",\"dateModified\":\"2025-11-10T01:52:22+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/#primaryimage\",\"url\":\"https:\\\/\\\/ars.els-cdn.com\\\/content\\\/image\\\/1-s2.0-S0160412021005420-gr5.jpg\",\"contentUrl\":\"https:\\\/\\\/ars.els-cdn.com\\\/content\\\/image\\\/1-s2.0-S0160412021005420-gr5.jpg\"},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/data\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Data\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/#website\",\"url\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/\",\"name\":\"Emory Environmental Remote Sensing Group\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/scholarblogs.emory.edu\\\/remote-sensing-group\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Data - Emory Environmental Remote Sensing Group","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/","og_locale":"en_US","og_type":"article","og_title":"Data - Emory Environmental Remote Sensing Group","og_description":"Below are the datasets our lab uses as well as curated.&nbsp; The paper citations for the datasets have been added as well. &nbsp; TROPOMI-derived ground ozone in California Using the TROPOMI satellite data and the HRRR meteorological feild, the daily-level ground ozone concentrations were estimated using random forest model. TROPOMI data improved the estimate of [&hellip;]","og_url":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/","og_site_name":"Emory Environmental Remote Sensing Group","article_modified_time":"2025-11-10T01:52:22+00:00","og_image":[{"url":"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg","type":"","width":"","height":""}],"twitter_card":"summary_large_image","twitter_misc":{"Est. reading time":"3 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/","url":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/","name":"Data - Emory Environmental Remote Sensing Group","isPartOf":{"@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/#website"},"primaryImageOfPage":{"@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/#primaryimage"},"image":{"@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/#primaryimage"},"thumbnailUrl":"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg","datePublished":"2024-11-04T05:01:57+00:00","dateModified":"2025-11-10T01:52:22+00:00","breadcrumb":{"@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/#primaryimage","url":"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg","contentUrl":"https:\/\/ars.els-cdn.com\/content\/image\/1-s2.0-S0160412021005420-gr5.jpg"},{"@type":"BreadcrumbList","@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/data\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/"},{"@type":"ListItem","position":2,"name":"Data"}]},{"@type":"WebSite","@id":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/#website","url":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/","name":"Emory Environmental Remote Sensing Group","description":"","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"}]}},"_links":{"self":[{"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/pages\/1586","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/users\/8813"}],"replies":[{"embeddable":true,"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/comments?post=1586"}],"version-history":[{"count":9,"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/pages\/1586\/revisions"}],"predecessor-version":[{"id":1702,"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/pages\/1586\/revisions\/1702"}],"wp:attachment":[{"href":"https:\/\/scholarblogs.emory.edu\/remote-sensing-group\/wp-json\/wp\/v2\/media?parent=1586"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}