{"id":2968451,"date":"2026-06-25T23:20:35","date_gmt":"2026-06-26T06:20:35","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2968451"},"modified":"2026-07-14T07:59:33","modified_gmt":"2026-07-14T14:59:33","slug":"analyze-solar-adoption-in-arcgis-online-part1","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1","title":{"rendered":"Analyzing solar adoption in ArcGIS Online Part1: Feature extraction with AI and World Imagery"},"author":372552,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":"1"},"categories":[22931],"tags":[758311,186132,780072,26391,778102],"industry":[],"product":[36581],"class_list":["post-2968451","blog","type-blog","status-publish","format-standard","hentry","category-imagery","tag-ai","tag-deep-learning","tag-lawrasteranalysis","tag-world-imagery","tag-worldimageryai","product-arcgis-living-atlas"],"acf":{"authors":[{"ID":372552,"user_firstname":"Jill","user_lastname":"Mamini","nickname":"Jill Mamini","user_nicename":"jmamini","display_name":"Jill Mamini","user_email":"jmamini@esri.com","user_url":"","user_registered":"2025-06-11 16:24:36","user_description":"Jill Mamini is a Principal GIS Engineer on the ArcGIS Living Atlas of the World Imagery team at Esri. She collaborates on the curation and publication of foundational online content and information products for ArcGIS Living Atlas.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/06\/profileforUC-465x465.png' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"related_articles":[{"ID":2645732,"post_author":"366412","post_date":"2025-02-11 15:50:28","post_date_gmt":"2025-02-11 23:50:28","post_content":"","post_title":"Use AI and World Imagery for feature extraction in ArcGIS Pro","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"learn-to-use-ai-to-extract-information-from-world-imagery","to_ping":"","pinged":"","post_modified":"2026-07-12 22:43:20","post_modified_gmt":"2026-07-13 05:43:20","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2645732","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":2970403,"post_author":"372552","post_date":"2026-06-26 15:09:31","post_date_gmt":"2026-06-26 22:09:31","post_content":"","post_title":"Analyzing solar adoption in ArcGIS Online Part2: Coverage analysis and insights","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"analyze-solar-adoption-in-arcgis-online-part2","to_ping":"","pinged":"","post_modified":"2026-07-21 15:45:09","post_modified_gmt":"2026-07-21 22:45:09","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2970403","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"}],"show_article_image":false,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Analyzing-solar-adoption-in-ArcGIS-Online-Card-826x465v2.jpg","wide_image":false,"short_description":"Learn an ArcGIS Online workflow to extract features from World Imagery and gain insights about solar power adoption in a community.","flexible_content":[{"acf_fc_layout":"image","image":{"ID":2974696,"id":2974696,"title":"Part1_Duration_Level_Credits_v2","filename":"Part1_Duration_Level_Credits_v2-scaled.png","filesize":35511,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-scaled.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/part1_duration_level_credits_v2","alt":"","author":"372552","description":"","caption":"","name":"part1_duration_level_credits_v2","status":"inherit","uploaded_to":2968451,"date":"2026-07-02 16:27:33","modified":"2026-07-02 16:27:33","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":320,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-scaled.png","medium-width":464,"medium-height":58,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-scaled.png","medium_large-width":768,"medium_large-height":96,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-scaled.png","large-width":1920,"large-height":240,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-1536x192.png","1536x1536-width":1536,"1536x1536-height":192,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-2048x256.png","2048x2048-width":2048,"2048x2048-height":256,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-826x103.png","card_image-width":826,"card_image-height":103,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1_Duration_Level_Credits_v2-1920x240.png","wide_image-width":1920,"wide_image-height":240}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>This two-part blog tutorial series is aimed at showing users how Living Atlas ready-to-use content and apps can be utilized in conjunction with ArcGIS Online analysis tools to gain insights into solar power adoption within a community. The end-to-end workflow is performed in a web browser for optimal accessibility.<\/p>\n<p>Part 1 of this workflow leverages ready-to-use AI tools and models in ArcGIS Online and ArcGIS Living Atlas to extract building footprints and rooftop solar panels from World Imagery.<\/p>\n<p><a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part2\">Part 2 of this workflow<\/a> continues using ArcGIS Online capabilities to calculate solar panel coverage on rooftops, and correlate buildings with demographic data available in Living Atlas. From this additional analysis, insights into solar power adoption within a community can be shared through a dashboard in ArcGIS Online.<\/p>\n"},{"acf_fc_layout":"content","content":"<h1 id=\"quick\"><\/h1>\n<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h3><strong>Quick links<\/strong><\/h3>\n<p>Use the links below to navigate different sections of this article.<\/p>\n<ul>\n<li><a href=\"#terms\">Terms of Use<\/a><\/li>\n<li><a href=\"#sysreqs\">System Requirements<\/a><\/li>\n<li><a href=\"#imageryselection\">Imagery Selection<\/a><\/li>\n<li><a href=\"#detectobjects\">Detect Objects using AI Deep Learning Models<\/a><\/li>\n<li><a href=\"#refiningresults\">Refining Results<\/a><\/li>\n<\/ul>\n<p><a href=\"#more\">More information<\/a><\/p>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>Terms of Use<\/strong><\/h2>\n<h2 id=\"terms\"><\/h2>\n"},{"acf_fc_layout":"content","content":"<p>World Imagery is available for automated information extraction under the following conditions:<\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">World Imagery layers\/services cannot be used as direct input to automated information extraction.<\/span><span data-contrast=\"auto\">\u00a0<\/span><span data-contrast=\"auto\">Users must export their area of interest to a tile package<\/span><span data-contrast=\"auto\">\u00a0or hosted tile layer<\/span><span data-contrast=\"auto\">\u00a0for use as input to information extraction processes.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span class=\"TrackChangeTextInsertion TrackedChange SCXW124529350 BCX8\"><span class=\"TextRun SCXW124529350 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW124529350 BCX8\">Tile packages\u00a0<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW124529350 BCX8\"><span class=\"TextRun SCXW124529350 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW124529350 BCX8\">and<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW124529350 BCX8\"><span class=\"TextRun SCXW124529350 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW124529350 BCX8\">\u00a0tile layers created from World Imagery layers\/services are strictly for use within ArcGIS.<\/span><\/span><\/span><span class=\"EOP Selected TrackedChange SCXW124529350 BCX8\" data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">Data and information<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">\u00a0derived from World Imagery layers, services, and tiles, including but not limited to vector and raster derivatives,\u00a0<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">are<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">\u00a0strictly for non-commercial use<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">\u00a0within ArcGIS<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW159307081 BCX8\"><span class=\"TextRun SCXW159307081 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW159307081 BCX8\">.<\/span><\/span><\/span><span class=\"EOP Selected TrackedChange SCXW159307081 BCX8\" data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559685&quot;:720,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Symbol&quot;,&quot;469769242&quot;:[8226],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;\uf0b7&quot;,&quot;469777815&quot;:&quot;multilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span class=\"TextRun SCXW49793348 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49793348 BCX8\">Each user <\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW49793348 BCX8\"><span class=\"TextRun SCXW49793348 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49793348 BCX8\">is required to<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW49793348 BCX8\"><span class=\"TextRun SCXW49793348 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49793348 BCX8\">\u00a0<\/span><\/span><\/span><span class=\"TextRun SCXW49793348 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW49793348 BCX8\">have an ArcGIS organizational account.<\/span><\/span><span class=\"EOP Selected SCXW49793348 BCX8\" data-ccp-props=\"{}\">\u00a0<\/span><\/li>\n<\/ul>\n"},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>System Requirements<\/strong><\/h2>\n<h2 id=\"sysreqs\"><\/h2>\n"},{"acf_fc_layout":"content","content":"<p><span class=\"TextRun SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW136113386 BCX8\">This workflow requires an ArcGIS organizational account, a minimum of a\u00a0<\/span><\/span><a class=\"Hyperlink TrackedChange TrackChangeHyperlinkInstruction SCXW136113386 BCX8\" href=\"https:\/\/www.esri.com\/en-us\/arcgis\/products\/user-types\/explore\/professional\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TrackChangeTextInsertion TrackedChange SCXW136113386 BCX8\"><span class=\"TextRun Underlined SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW136113386 BCX8\" data-ccp-charstyle=\"Hyperlink\">Professional\u00a0<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW136113386 BCX8\"><span class=\"TextRun Underlined SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun CommentStart CommentHighlightPipeRest CommentHighlightRest SCXW136113386 BCX8\" data-ccp-charstyle=\"Hyperlink\">user type<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun CommentHighlightRest SCXW136113386 BCX8\">\u00a0and\u00a0<\/span><\/span><a class=\"Hyperlink TrackedChange TrackChangeHyperlinkInstruction SCXW136113386 BCX8\" href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/administer\/member-roles.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TrackChangeTextInsertion TrackedChange SCXW136113386 BCX8\"><span class=\"TextRun Underlined SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun CommentHighlightRest SCXW136113386 BCX8\" data-ccp-charstyle=\"Hyperlink\">Publisher\u00a0<\/span><\/span><\/span><span class=\"TrackChangeTextInsertion TrackedChange SCXW136113386 BCX8\"><span class=\"TextRun Underlined SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun CommentHighlightPipeRest SCXW136113386 BCX8\" data-ccp-charstyle=\"Hyperlink\">role<\/span><\/span><\/span><\/a><span class=\"TextRun SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW136113386 BCX8\">\u00a0and involves raster analysis in ArcGIS Online which consumes\u202f<\/span><\/span><a class=\"Hyperlink SCXW136113386 BCX8\" href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/administer\/credits.htm\" target=\"_blank\" rel=\"noreferrer noopener\"><span class=\"TextRun Underlined SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"none\"><span class=\"NormalTextRun SCXW136113386 BCX8\" data-ccp-charstyle=\"Hyperlink\">credits<\/span><\/span><\/a><span class=\"TextRun SCXW136113386 BCX8\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW136113386 BCX8\">.<\/span><\/span><span class=\"EOP Selected SCXW136113386 BCX8\" data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n"},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>Imagery Selection<\/strong><\/h2>\n<h1 id=\"imageryselection\"><\/h1>\n"},{"acf_fc_layout":"content","content":"<p>One key to this workflow is high-resolution aerial imagery from Nearmap. This imagery provides detail and clarity for reliable automated information extraction of features such as rooftop solar panels. Starting in the second half of 2026, Nearmap 20 cm. vertical imagery will begin to be integrated and regularly updated in World Imagery for 200 cities across the United States, Canada, Australia and New Zealand. You can read more about that <a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/whats-new-in-world-imagery-july-2026\">here<\/a>.<\/p>\n<p>The workflow begins in the World Imagery Wayback app, where a new capability allows users to publish a hosted Tile Layer in their ArcGIS Online organization.<\/p>\n<p><strong>Step 1<\/strong> &#8211; Open the Wayback app at the specified extent of this tutorial by clicking this link:\u00a0 <a href=\"https:\/\/livingatlas.arcgis.com\/wayback\/#mapCenter=-117.15142%2C34.05391%2C16&amp;mode=explore&amp;active=39767\">Wayback in Redlands, CA<\/a><\/p>\n<p>Note: If you are not already signed in at this point, you will be prompted to authenticate with your ArcGIS Online account.<\/p>\n<ol>\n<li style=\"list-style-type: none\">\n<ol>\n<li style=\"list-style-type: none\">\n<ol>\n<li style=\"list-style-type: none\">\n<ol>\n<li>Verify that the Wayback version 2024-06-07 is selected<\/li>\n<li>Click on the map to validate the source:\u00a0 imagery provider, capture date and spatial resolution.<\/li>\n<li>Click Export a Tile Package for the selected version.<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2973043,"id":2973043,"title":"exportTile","filename":"exportTile.png","filesize":4226120,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/exporttile","alt":"","author":"372552","description":"","caption":"","name":"exporttile","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 03:44:44","modified":"2026-06-25 03:44:44","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":2009,"height":1080,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile.png","medium-width":464,"medium-height":249,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile.png","medium_large-width":768,"medium_large-height":413,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile.png","large-width":1920,"large-height":1032,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile-1536x826.png","1536x1536-width":1536,"1536x1536-height":826,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile.png","2048x2048-width":2009,"2048x2048-height":1080,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile-826x444.png","card_image-width":826,"card_image-height":444,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/exportTile-1920x1032.png","wide_image-width":1920,"wide_image-height":1032}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 2 &#8211;<\/strong> Export Tile Package<\/p>\n<ol>\n<li>For the purposes of this tutorial, please leave the <strong>default extent. <\/strong>Tile export does allow the user to refine the geographic extent by selecting and dragging a corner.<\/li>\n<li>Please select Level 20 as the max level of detail.<\/li>\n<li>Create Tile Package.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2972850,"id":2972850,"title":"Tutorial_TileExportSettings","filename":"Tutorial_TileExportSettings.png","filesize":71502,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/tutorial_tileexportsettings","alt":"","author":"372552","description":"","caption":"","name":"tutorial_tileexportsettings","status":"inherit","uploaded_to":2968451,"date":"2026-06-24 21:29:43","modified":"2026-06-24 21:29:43","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":518,"height":483,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","medium-width":280,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","medium_large-width":518,"medium_large-height":483,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","large-width":518,"large-height":483,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","1536x1536-width":518,"1536x1536-height":483,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","2048x2048-width":518,"2048x2048-height":483,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings-499x465.png","card_image-width":499,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Tutorial_TileExportSettings.png","wide_image-width":518,"wide_image-height":483}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p style=\"text-align: center\"><strong>New Capability in the Wayback Application!\u00a0<\/strong><\/p>\n<p>&nbsp;<\/p>\n<p><strong>Step 3<\/strong> &#8211; When prompted, select <strong>Publish as Tile Layer<\/strong> in your ArcGIS Online organization.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2969968,"id":2969968,"title":"waybackPubtilelayer","filename":"waybackPubtilelayer.png","filesize":55204,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/waybackpubtilelayer","alt":"","author":"372552","description":"","caption":"","name":"waybackpubtilelayer","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 19:50:01","modified":"2026-06-12 19:50:01","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":434,"height":448,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","medium-width":253,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","medium_large-width":434,"medium_large-height":448,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","large-width":434,"large-height":448,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","1536x1536-width":434,"1536x1536-height":448,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","2048x2048-width":434,"2048x2048-height":448,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","card_image-width":434,"card_image-height":448,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/waybackPubtilelayer.png","wide_image-width":434,"wide_image-height":448}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>When the hosted Tile Layer is ready, you will be prompted to Open the Tile Layer&#8217;s ArcGIS Online item page directly from the Wayback Application.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2969970,"id":2969970,"title":"WayBackOpenTileLayer","filename":"WayBackOpenTileLayer.png","filesize":46117,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/waybackopentilelayer","alt":"","author":"372552","description":"","caption":"","name":"waybackopentilelayer","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 19:57:06","modified":"2026-06-12 19:57:06","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":428,"height":326,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","medium-width":343,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","medium_large-width":428,"medium_large-height":326,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","large-width":428,"large-height":326,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","1536x1536-width":428,"1536x1536-height":326,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","2048x2048-width":428,"2048x2048-height":326,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","card_image-width":428,"card_image-height":326,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/WayBackOpenTileLayer.png","wide_image-width":428,"wide_image-height":326}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 4<\/strong> &#8211; From the ArcGIS Online item page, you can see details about the hosted World Imagery Tile Layer and open it in Map Viewer.<\/p>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2969975,"id":2969975,"title":"OpeninMapViewer","filename":"OpeninMapViewer.png","filesize":324189,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/openinmapviewer","alt":"","author":"372552","description":"","caption":"","name":"openinmapviewer","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 19:59:52","modified":"2026-06-12 19:59:52","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":1893,"height":690,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","medium-width":464,"medium-height":169,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","medium_large-width":768,"medium_large-height":280,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","large-width":1893,"large-height":690,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer-1536x560.png","1536x1536-width":1536,"1536x1536-height":560,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","2048x2048-width":1893,"2048x2048-height":690,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer-826x301.png","card_image-width":826,"card_image-height":301,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/OpeninMapViewer.png","wide_image-width":1893,"wide_image-height":690}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/arcgis-content.maps.arcgis.com\/home\/item.html?id=39d1125df99247768003027f6a7188d8"},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>Detect Objects using AI Deep Learning Models<\/strong><\/h2>\n<h1 id=\"detectobjects\"><\/h1>\n"},{"acf_fc_layout":"content","content":"<p><span data-contrast=\"auto\">With the World Imagery tile layer as source input, we can leverage pre-trained deep learning models available in Living Atlas, and ArcGIS Online ready-to-use analysis tools to detect and extract:<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559685&quot;:0,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:278}\">\u00a0<\/span><\/p>\n<ul>\n<li data-leveltext=\"o\" data-font=\"Courier New\" data-listid=\"10\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:1440,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Courier New&quot;,&quot;469769242&quot;:[9675],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;o&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"2\"><span data-contrast=\"auto\">Building Footprints<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:278}\">\u00a0<\/span><\/li>\n<li data-leveltext=\"o\" data-font=\"Courier New\" data-listid=\"10\" data-list-defn-props=\"{&quot;335552541&quot;:1,&quot;335559683&quot;:1,&quot;335559684&quot;:-2,&quot;335559685&quot;:1440,&quot;335559991&quot;:360,&quot;469769226&quot;:&quot;Courier New&quot;,&quot;469769242&quot;:[9675],&quot;469777803&quot;:&quot;left&quot;,&quot;469777804&quot;:&quot;o&quot;,&quot;469777815&quot;:&quot;hybridMultilevel&quot;}\" data-aria-posinset=\"1\" data-aria-level=\"2\"><span data-contrast=\"auto\">Solar Panels<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;201341983&quot;:0,&quot;335551550&quot;:1,&quot;335551620&quot;:1,&quot;335559737&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:160,&quot;335559740&quot;:278}\">\u00a0<\/span><\/li>\n<\/ul>\n<p>In order to limit the time it takes to complete this tutorial and the number of credits it consumes, you will use a publicly hosted feature layer to define the processing extents for object detection and extraction.<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Step 1<\/strong> &#8211; Search ArcGIS Online for the processing extent feature layer and add it to a map<\/p>\n<ol>\n<li>Click on the <strong>+<\/strong> <strong>icon<\/strong> to add a layer to your web map<\/li>\n<li>Select <strong>ArcGIS Online<\/strong> from the dropdown menu<\/li>\n<li><strong>Search<\/strong> for <em>FeatureExtraction_ProcessingExtent<\/em><\/li>\n<li><strong>Add<\/strong> the Layer to the map<\/li>\n<li><strong>Save<\/strong> the web map<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2973391,"id":2973391,"title":"AddProcessingExtent2Map","filename":"AddProcessingExtent2Map.png","filesize":58243,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/addprocessingextent2map","alt":"","author":"372552","description":"","caption":"","name":"addprocessingextent2map","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 21:55:31","modified":"2026-06-25 21:55:31","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":593,"height":427,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","medium-width":362,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","medium_large-width":593,"medium_large-height":427,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","large-width":593,"large-height":427,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","1536x1536-width":593,"1536x1536-height":427,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","2048x2048-width":593,"2048x2048-height":427,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","card_image-width":593,"card_image-height":427,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AddProcessingExtent2Map.png","wide_image-width":593,"wide_image-height":427}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>&nbsp;<\/p>\n<p><strong>Step 2 &#8211;<\/strong> Access the ArcGIS Online Analysis Detect Objects using Deep Learning Tool<\/p>\n<ol>\n<li>Select the Analysis Button from the right-hand side of Map Viewer<\/li>\n<li>Select Tools<\/li>\n<li>Search for tool using a key word &#8220;detect&#8221;<\/li>\n<li>Select the<strong> Detect Objects Using Deep Learning<\/strong><\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2969840,"id":2969840,"title":"AnalysisToolSearch","filename":"AnalysisToolSearch.png","filesize":51903,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/analysistoolsearch","alt":"Analysis Tools Search","author":"372552","description":"","caption":"","name":"analysistoolsearch","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 15:13:06","modified":"2026-06-12 15:13:20","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":444,"height":590,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","medium-width":196,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","medium_large-width":444,"medium_large-height":590,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","large-width":444,"large-height":590,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","1536x1536-width":444,"1536x1536-height":590,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","2048x2048-width":444,"2048x2048-height":590,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch-350x465.png","card_image-width":350,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/AnalysisToolSearch.png","wide_image-width":444,"wide_image-height":590}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 3 &#8211;<\/strong> Specify the Inputs for the Detect Objects using Deep Learning Tool<\/p>\n<ol>\n<li>Select your World Imagery tile layer as the <strong>Input imagery layer<\/strong><\/li>\n<li>Click <strong>Select model\u00a0<\/strong>under Model Settings<\/li>\n<li>Select <strong>Living Atlas<\/strong> from the dropdown menu<\/li>\n<li>Search for the model using the keyword &#8220;<strong>Building<\/strong>&#8220;<\/li>\n<li>Select the <strong>Building Footprint Extraction &#8211; USA<\/strong> pre-trained deep learning package<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2969977,"id":2969977,"title":"detectInputs","filename":"detectInputs.png","filesize":55828,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/detectinputs","alt":"","author":"372552","description":"","caption":"","name":"detectinputs","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 20:04:30","modified":"2026-06-12 20:04:30","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":446,"height":654,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","medium-width":178,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","medium_large-width":446,"medium_large-height":654,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","large-width":446,"large-height":654,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","1536x1536-width":446,"1536x1536-height":654,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","2048x2048-width":446,"2048x2048-height":654,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs-317x465.png","card_image-width":317,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","wide_image-width":446,"wide_image-height":654}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":2969853,"id":2969853,"title":"SelectModel456","filename":"SelectModel456.png","filesize":83742,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/selectmodel456","alt":"","author":"372552","description":"","caption":"","name":"selectmodel456","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 15:43:26","modified":"2026-06-12 15:43:26","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":1350,"height":619,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","medium-width":464,"medium-height":213,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","medium_large-width":768,"medium_large-height":352,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","large-width":1350,"large-height":619,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","1536x1536-width":1350,"1536x1536-height":619,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","2048x2048-width":1350,"2048x2048-height":619,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456-826x379.png","card_image-width":826,"card_image-height":379,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/SelectModel456.png","wide_image-width":1350,"wide_image-height":619}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>OPTIONAL &#8211; <\/strong>When the model is loaded, a set of default values for the parameters will be given. The default values tend to perform well on their own, but some modification could improve performance and results. To understand what each argument does, hover over the information icon next to the <strong>Model arguments<\/strong> subheading and read the short description.<\/p>\n<ul>\n<li>Lowering the default value for<strong> padding<\/strong> may increase performance.<\/li>\n<li>Increasing <strong>tile size<\/strong> may provide better results detecting larger objects.<\/li>\n<li>Lowering the <strong>threshold<\/strong> may help improve object detection.<\/li>\n<\/ul>\n<p><strong>Step 4<\/strong> &#8211; Configure the Deep Learning Model Arguments<\/p>\n<ol>\n<li>Model Arguments &#8211; use the defaults except reduce the <strong>Threshold<\/strong> to 0.4<\/li>\n<li>Turn non maximum suppression <strong>NMS ON<\/strong>. This will consolidate detected objects by removing duplicates.<\/li>\n<li>Specify an <strong>Output Name\u00a0<\/strong> Tutorial_Building_Footprints, and location for the detected objects layer.<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2973373,"id":2973373,"title":"model_arguments_numbered_v2","filename":"model_arguments_numbered_v2.png","filesize":57949,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/model_arguments_numbered_v2","alt":"","author":"372552","description":"","caption":"","name":"model_arguments_numbered_v2","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 21:36:37","modified":"2026-06-25 21:36:37","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":445,"height":692,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","medium-width":168,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","medium_large-width":445,"medium_large-height":692,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","large-width":445,"large-height":692,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","1536x1536-width":445,"1536x1536-height":692,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","2048x2048-width":445,"2048x2048-height":692,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2-299x465.png","card_image-width":299,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_v2.png","wide_image-width":445,"wide_image-height":692}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 5<\/strong>&#8211; Configure outputs &amp; environment settings, estimate credits and run the model<\/p>\n<ol>\n<li>Expand the <strong>Environment Settings<\/strong><\/li>\n<li>Set the processing extent to <strong>Layer<\/strong><\/li>\n<li>Specify the <em>FeatureExtraction_ProcessingExtent<\/em> layer<\/li>\n<li>For <strong>Cell size<\/strong> specify a value of <strong>0.20\u00a0<\/strong><\/li>\n<li><strong>Estimate Credits<\/strong>.<\/li>\n<li>Click<strong> Run<\/strong> to submit the job.<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2973379,"id":2973379,"title":"ProcessingExtents","filename":"ProcessingExtents.png","filesize":101175,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/processingextents","alt":"","author":"372552","description":"","caption":"","name":"processingextents","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 21:39:11","modified":"2026-06-25 21:39:11","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":521,"height":1017,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","medium-width":134,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","medium_large-width":521,"medium_large-height":1017,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","large-width":521,"large-height":1017,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","1536x1536-width":521,"1536x1536-height":1017,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","2048x2048-width":521,"2048x2048-height":1017,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents-238x465.png","card_image-width":238,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","wide_image-width":521,"wide_image-height":1017}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>Online resources are provisioned and the deep learning model executed with the World Imagery Tile Layer as the source. The process takes time to process and produce results. When completed, the results from\u00a0the<a href=\"https:\/\/arcgis-content.maps.arcgis.com\/home\/item.html?id=a6857359a1cd44839781a4f113cd5934\"><strong> Building Footprint Extraction -USA<\/strong><\/a> deep learning package with the World Imagery Tile Layer will be loaded in Map Viewer.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2973051,"id":2973051,"title":"JustBuildings","filename":"JustBuildings.png","filesize":1908642,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/justbuildings","alt":"","author":"372552","description":"","caption":"","name":"justbuildings","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 04:04:46","modified":"2026-06-25 04:04:46","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":984,"height":796,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","medium-width":323,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","medium_large-width":768,"medium_large-height":621,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","large-width":984,"large-height":796,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","1536x1536-width":984,"1536x1536-height":796,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","2048x2048-width":984,"2048x2048-height":796,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings-575x465.png","card_image-width":575,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustBuildings.png","wide_image-width":984,"wide_image-height":796}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/arcgis-content.maps.arcgis.com\/home\/item.html?id=cd19714a3810437db64c11249e9097f3"},{"acf_fc_layout":"content","content":"<p>Once a Detect Objects using Deep Learning job has been submitted, you can configure another job for submission. You do not need to wait for the first submitted job to finish.<\/p>\n<p>Follow the same <strong>Detect Objects using AI Deep Learning Models Steps 3 through 5<\/strong> for detecting solar panels instead of footprints. Steps 1 and 2 will be the same as they were for when you were detecting building footprints.<\/p>\n<p><strong>Step 3 &#8211;<\/strong> Specify the Inputs for the Detect Objects using Deep Learning Tool<\/p>\n<ol>\n<li>Select your World Imagery tile layer as the <strong>Input imagery layer<\/strong><\/li>\n<li>Click <strong>Select model\u00a0<\/strong>under Model Settings<\/li>\n<li>Select <strong>Living Atlas<\/strong> from the dropdown menu<\/li>\n<li>Search for the model using the keyword &#8220;<strong>Solar<\/strong>&#8220;<\/li>\n<li>Select the <strong>Solar Panel Detection &#8211; USA<\/strong>\u00a0pre-trained deep learning package<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2969977,"id":2969977,"title":"detectInputs","filename":"detectInputs.png","filesize":55828,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/detectinputs","alt":"","author":"372552","description":"","caption":"","name":"detectinputs","status":"inherit","uploaded_to":2968451,"date":"2026-06-12 20:04:30","modified":"2026-06-12 20:04:30","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":446,"height":654,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","medium-width":178,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","medium_large-width":446,"medium_large-height":654,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","large-width":446,"large-height":654,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","1536x1536-width":446,"1536x1536-height":654,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","2048x2048-width":446,"2048x2048-height":654,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs-317x465.png","card_image-width":317,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/detectInputs.png","wide_image-width":446,"wide_image-height":654}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":2974049,"id":2974049,"title":"solarpanelusamodel","filename":"solarpanelusamodel.png","filesize":50859,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/solarpanelusamodel","alt":"","author":"372552","description":"","caption":"","name":"solarpanelusamodel","status":"inherit","uploaded_to":2968451,"date":"2026-06-30 00:00:20","modified":"2026-06-30 00:00:20","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":1343,"height":403,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","medium-width":464,"medium-height":139,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","medium_large-width":768,"medium_large-height":230,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","large-width":1343,"large-height":403,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","1536x1536-width":1343,"1536x1536-height":403,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","2048x2048-width":1343,"2048x2048-height":403,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel-826x248.png","card_image-width":826,"card_image-height":248,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/solarpanelusamodel.png","wide_image-width":1343,"wide_image-height":403}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 4<\/strong>\u00a0\u2013 Configure the Deep Learning Model Arguments<\/p>\n<ol>\n<li>Model Arguments &#8211; use the defaults except reduce the <strong>Threshold<\/strong> to 0.1<\/li>\n<li>Turn non maximum suppression\u00a0<strong>NMS ON<\/strong>. This will consolidate detected objects by removing duplicates.<\/li>\n<li>Specify an <strong>Output Name<\/strong> Tutorial_Solar_Panels, and location for the detected objects layer.<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2974056,"id":2974056,"title":"model_arguments_numbered_Solarv2","filename":"model_arguments_numbered_Solarv2.png","filesize":51349,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/model_arguments_numbered_solarv2","alt":"","author":"372552","description":"","caption":"","name":"model_arguments_numbered_solarv2","status":"inherit","uploaded_to":2968451,"date":"2026-06-30 00:24:40","modified":"2026-06-30 00:24:40","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":476,"height":591,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","medium-width":210,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","medium_large-width":476,"medium_large-height":591,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","large-width":476,"large-height":591,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","1536x1536-width":476,"1536x1536-height":591,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","2048x2048-width":476,"2048x2048-height":591,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2-375x465.png","card_image-width":375,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/model_arguments_numbered_Solarv2.png","wide_image-width":476,"wide_image-height":591}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><strong>Step 5<\/strong>\u2013 Configure outputs &amp; environment settings, estimate credits and run the model<\/p>\n<ol>\n<li>Expand the\u00a0<strong>Environment Settings<\/strong><\/li>\n<li>Set the <strong>Processing extent<\/strong> to Layer<\/li>\n<li><b>Add Layer<\/b>\u00a0<em>FeatureExtraction_ProcessingExtent<\/em><\/li>\n<li>For\u00a0<strong>Cell size<\/strong>\u00a0specify a value of\u00a0<strong>0.20\u00a0<\/strong><\/li>\n<li><strong>Estimate Credits<\/strong>.<\/li>\n<li>Click<strong>\u00a0Run<\/strong>\u00a0to submit the job.<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2973379,"id":2973379,"title":"ProcessingExtents","filename":"ProcessingExtents.png","filesize":101175,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/processingextents","alt":"","author":"372552","description":"","caption":"","name":"processingextents","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 21:39:11","modified":"2026-06-25 21:39:11","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":521,"height":1017,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","medium-width":134,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","medium_large-width":521,"medium_large-height":1017,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","large-width":521,"large-height":1017,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","1536x1536-width":521,"1536x1536-height":1017,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","2048x2048-width":521,"2048x2048-height":1017,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents-238x465.png","card_image-width":238,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/ProcessingExtents.png","wide_image-width":521,"wide_image-height":1017}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>When completed, the results from the <a href=\"https:\/\/arcgis-content.maps.arcgis.com\/home\/item.html?id=c2508d72f2614104bfcfd5ccf1429284\"><strong>Solar Panel Detection &#8211; USA<\/strong><\/a> deep learning package with the World Imagery Tile Layer will be loaded in Map Viewer.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2973057,"id":2973057,"title":"JustSolarPanels","filename":"JustSolarPanels.png","filesize":1989131,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/justsolarpanels","alt":"","author":"372552","description":"","caption":"","name":"justsolarpanels","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 04:46:25","modified":"2026-06-25 04:46:25","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":992,"height":798,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","medium-width":324,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","medium_large-width":768,"medium_large-height":618,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","large-width":992,"large-height":798,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","1536x1536-width":992,"1536x1536-height":798,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","2048x2048-width":992,"2048x2048-height":798,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels-578x465.png","card_image-width":578,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/JustSolarPanels.png","wide_image-width":992,"wide_image-height":798}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>Refining Results<\/strong><\/h2>\n<h2 id=\"refiningresults\"><\/h2>\n"},{"acf_fc_layout":"content","content":"<p>AI with World Imagery was executed with two different pre-trained deep learning models available in the Living Atlas.\u00a0 In order to better visualize the results, you can stylize the symbology for each layer, to maximize contrast between the detected building footprints and the solar panels.<\/p>\n<p><strong>Step 1<\/strong> &#8211; Style selected layer symbology<\/p>\n<ol>\n<li>\u00a0Click on the <strong>Style<\/strong> icon<\/li>\n<li>Click on the <strong>Symbol style<\/strong> edit pencil icon<\/li>\n<li>Select a new<strong> Fill color\u00a0<\/strong><\/li>\n<li>Select an new <strong>Outline color<\/strong><\/li>\n<li>Click<strong> Done<\/strong> to apply the changes to symbology<\/li>\n<\/ol>\n<p>&nbsp;<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2973060,"id":2973060,"title":"Symbology","filename":"Symbology.png","filesize":228694,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/symbology-18","alt":"","author":"372552","description":"","caption":"","name":"symbology-18","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 04:56:45","modified":"2026-06-25 04:56:45","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":991,"height":842,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","medium-width":307,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","medium_large-width":768,"medium_large-height":653,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","large-width":991,"large-height":842,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","1536x1536-width":991,"1536x1536-height":842,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","2048x2048-width":991,"2048x2048-height":842,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology-547x465.png","card_image-width":547,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Symbology.png","wide_image-width":991,"wide_image-height":842}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p>Apply Symbology changes to make the solar panel result layers purple, and the building footprint results layer a bright blue. Display the solar panels on top of the building footprints and overlay both layers on the World Imagery tile layer they were extracted from.<\/p>\n<p><strong>Step 2<\/strong> &#8211; Save the web map<\/p>\n<ol>\n<li><strong>Rename<\/strong> the web map:<em> Part 1 &#8211; Feature Extraction Using AI with World Imagery<\/em><\/li>\n<li>Click on the<strong> Save<\/strong> Option on the left-hand toolbar of Map Viewer<\/li>\n<\/ol>\n"},{"acf_fc_layout":"image","image":{"ID":2973061,"id":2973061,"title":"Part1WebMap","filename":"Part1WebMap.png","filesize":1784291,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\/part1webmap","alt":"","author":"372552","description":"","caption":"","name":"part1webmap","status":"inherit","uploaded_to":2968451,"date":"2026-06-25 05:12:22","modified":"2026-06-25 05:12:22","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":1461,"height":785,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","medium-width":464,"medium-height":249,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","medium_large-width":768,"medium_large-height":413,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","large-width":1461,"large-height":785,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","1536x1536-width":1461,"1536x1536-height":785,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","2048x2048-width":1461,"2048x2048-height":785,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap-826x444.png","card_image-width":826,"card_image-height":444,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Part1WebMap.png","wide_image-width":1461,"wide_image-height":785}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"<p><img decoding=\"async\" src=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/03\/breakgray.png\" alt=\"\" \/><\/p>\n<h2><strong>More Information<\/strong><\/h2>\n<h2 id=\"more\"><\/h2>\n"},{"acf_fc_layout":"content","content":"<p>To extend the analysis beyond a single point in time, use the Wayback Application to explore historical versions of the World Imagery basemap. This allows you to identify older, high-resolution imagery for the same area of interest and apply the same AI workflow to extract building and solar panel features.<\/p>\n<p>By running deep learning models on multiple points in time, you can begin to introduce a temporal dimension to your analysis. This historical perspective enables you to compare change over time and provides valuable context for understanding patterns such as growth in solar adoption within a community.<\/p>\n"},{"acf_fc_layout":"content","content":"<p>Explore<a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part2\">\u00a0Part2: Coverage analysis and insights<\/a> to continue using ArcGIS Online ready-to-use capabilities to perform analysis of detected objects and correlate that information with demographic data available in Living Atlas.<\/p>\n<p>&nbsp;<\/p>\n<p>&nbsp;<\/p>\n"}]},"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.9 (Yoast SEO v25.9) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Analyzing solar adoption in ArcGIS Online Part1: Feature extraction with AI and World Imagery<\/title>\n<meta name=\"description\" content=\"This workflow will show you how to create a World Imagery hosted tile layer in your ArcGIS Online Organization directly from the Wayback Application. Go on to leverage Map Viewer Analysis Tools to use pretrained AI models from the Living Atlas to detect objects from World Imagery. The tutorial will outline how to derive metrics of the detected objects and gain insights about solar power adoption in a community.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Analyzing solar adoption in ArcGIS Online Part1: Feature extraction with AI and World Imagery\" \/>\n<meta property=\"og:description\" content=\"This workflow will show you how to create a World Imagery hosted tile layer in your ArcGIS Online Organization directly from the Wayback Application. Go on to leverage Map Viewer Analysis Tools to use pretrained AI models from the Living Atlas to detect objects from World Imagery. The tutorial will outline how to derive metrics of the detected objects and gain insights about solar power adoption in a community.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\" \/>\n<meta property=\"og:site_name\" content=\"ArcGIS Blog\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/esrigis\/\" \/>\n<meta property=\"article:modified_time\" content=\"2026-07-14T14:59:33+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/06\/Analyzing-solar-adoption-in-ArcGIS-Online-Card-826x465v2.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"826\" \/>\n\t<meta property=\"og:image:height\" content=\"465\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@ESRI\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"13 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":[\"Article\",\"BlogPosting\"],\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\"},\"author\":{\"name\":\"Jill Mamini\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/be091405a7be1969b147463cb6892585\"},\"headline\":\"Analyzing solar adoption in ArcGIS Online Part1: Feature extraction with AI and World Imagery\",\"datePublished\":\"2026-06-26T06:20:35+00:00\",\"dateModified\":\"2026-07-14T14:59:33+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\"},\"wordCount\":14,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#organization\"},\"keywords\":[\"AI\",\"deep learning\",\"lawrasteranalysis\",\"World Imagery\",\"worldimageryai\"],\"articleSection\":[\"Imagery &amp; Remote Sensing\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\",\"url\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/imagery\/analyze-solar-adoption-in-arcgis-online-part1\",\"name\":\"Analyzing solar adoption in ArcGIS Online Part1: Feature extraction with AI and World Imagery\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#website\"},\"datePublished\":\"2026-06-26T06:20:35+00:00\",\"dateModified\":\"2026-07-14T14:59:33+00:00\",\"description\":\"This workflow will show you how to create a World Imagery hosted tile layer in your ArcGIS Online Organization directly from the Wayback Application. 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