{"id":2968882,"date":"2026-06-04T12:05:43","date_gmt":"2026-06-04T19:05:43","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2968882"},"modified":"2026-07-07T13:40:17","modified_gmt":"2026-07-07T20:40:17","slug":"using-living-atlas-of-the-world-data-to-create-a-heat-risk-index","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/using-living-atlas-of-the-world-data-to-create-a-heat-risk-index","title":{"rendered":"Mapping Intra-Urban Surface Heat Islands \u2013 Part 2: Heat Risk Analysis and Insights"},"author":366412,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22931],"tags":[780062,557702,780072,40161,771442],"industry":[],"product":[36581],"class_list":["post-2968882","blog","type-blog","status-publish","format-standard","hentry","category-imagery","tag-analysisoptimized","tag-imagery-and-remote-sensing","tag-lawrasteranalysis","tag-living-atlas-of-the-world","tag-urban-heat-island","product-arcgis-living-atlas"],"acf":{"authors":[{"ID":366412,"user_firstname":"Hayden","user_lastname":"Hoffmeister","nickname":"Hayden Hoffmeister","user_nicename":"hhoffmeister","display_name":"Hayden Hoffmeister","user_email":"hhoffmeister@esri.com","user_url":"","user_registered":"2024-12-17 22:25:35","user_description":"","user_avatar":""},{"ID":270422,"user_firstname":"James","user_lastname":"Sill","nickname":"James Sill","user_nicename":"jsill","display_name":"James Sill","user_email":"JSill@esri.com","user_url":"","user_registered":"2021-08-30 15:08:30","user_description":"James is Product Engineer for Imagery Analytics at Esri. James' work is focused on expanding Earth Observation data and analytics available in the Living Atlas. He has a passion for using modern remote sensing, machine learning, and cloud computing to help the scientific and conservation community to gain a better understanding of our planet.","user_avatar":""}],"short_description":"Using Living Atlas of the World Data to Create a Heat Risk Index","flexible_content":[{"acf_fc_layout":"content","content":"

Enabling communities around the world with on-demand urban heat mapping.<\/h2>\n"},{"acf_fc_layout":"image","image":{"ID":2974677,"id":2974677,"title":"information_header_redux","filename":"information_header_redux-scaled.png","filesize":42485,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/using-living-atlas-of-the-world-data-to-create-a-heat-risk-index\/information_header_redux","alt":"","author":"366412","description":"","caption":"","name":"information_header_redux","status":"inherit","uploaded_to":2968882,"date":"2026-07-02 15:59:42","modified":"2026-07-02 15:59:42","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":2560,"height":295,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-scaled.png","medium-width":464,"medium-height":53,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-scaled.png","medium_large-width":768,"medium_large-height":89,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-scaled.png","large-width":1920,"large-height":221,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-1536x177.png","1536x1536-width":1536,"1536x1536-height":177,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-2048x236.png","2048x2048-width":2048,"2048x2048-height":236,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-826x95.png","card_image-width":826,"card_image-height":95,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/information_header_redux-1920x221.png","wide_image-width":1920,"wide_image-height":221}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Heat waves and urban heat island effects are increasing heat-related illnesses and deaths worldwide. According to the World Health Organization<\/a>, heat-related deaths among people over age 65 increased by 85% between 2000 and 2021. While individuals can take steps to protect themselves from extreme heat, city planners and landscape architects can reduce heat risk across entire communities by decreasing paved surfaces, increasing water features, and planting more trees and vegetation. These strategies can be highly effective but are often expensive, making it important to understand where heat risk is greatest so resources can be targeted effectively.<\/p>\n

In Part 1<\/a> of this blog series, you learned how to utilize Landsat Level-2 multispectral imagery to map urban heat islands, but that only tells part of the story. In this blog, you will utilize ArcGIS Living Atlas of the World data, as well as the tools available in ArcGIS Online Map Viewer, to map out an urban heat risk index of Monterrey, Mexico. With this data, you’ll be able to garner a broader understanding of where the urban area is most vulnerable to heat risk.<\/p>\n"},{"acf_fc_layout":"content","content":"

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Quick links<\/strong><\/h3>\n

Use the links below to navigate to different sections of this article.<\/p>\n