{"id":2246572,"date":"2024-02-28T22:10:24","date_gmt":"2024-02-29T06:10:24","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2246572"},"modified":"2024-02-29T10:51:50","modified_gmt":"2024-02-29T18:51:50","slug":"introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer","title":{"rendered":"Introducing the Calculate Composite Index Tool in ArcGIS Online Map Viewer"},"author":10232,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,37101],"tags":[769372,33371,770492,25581,773282],"industry":[],"product":[36551],"class_list":["post-2246572","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-announcements","tag-composite-index","tag-map-viewer","tag-map-viewer-analysis","tag-spatial-statistics","tag-whats-new-february-2024","product-arcgis-online"],"acf":{"short_description":"Create indices measuring risk, equity, vulnerability, and more, using the new Calculate Composite Index tool in ArcGIS Online Map Viewer.","flexible_content":[{"acf_fc_layout":"content","content":"

With the February 2024 release of ArcGIS Online, you can now use the Calculate Composite Index tool<\/a> in analysis in Map Viewer<\/a>. Let\u2019s use the tool to create an Urban Heat Risk Index for Washington D.C., to identify which census tracts might be at the greatest risk of the adverse impacts of extreme heat events.<\/p>\n

First, we\u2019ll grab the U.S. Urban Heat Island Mapping Campaign<\/a> layer from the Living Atlas. This layer includes variables about temperature and demographics for several cities in the U.S.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256552,"id":2256552,"title":"CCI_1","filename":"CCI_1.png","filesize":24806,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_1","alt":"The U.S. Urban Heat Island Mapping Campaign layer in the Map Viewer","author":"10232","description":"","caption":"","name":"cci_1","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:43:06","modified":"2024-02-26 22:43:58","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":383,"height":252,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","medium-width":383,"medium-height":252,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","medium_large-width":383,"medium_large-height":252,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","large-width":383,"large-height":252,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","1536x1536-width":383,"1536x1536-height":252,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","2048x2048-width":383,"2048x2048-height":252,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","card_image-width":383,"card_image-height":252,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_1.png","wide_image-width":383,"wide_image-height":252}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Zooming in to Washington D.C. we can see the afternoon temperature anomaly \u2013 this shows how the neighborhood temperature compares to the city-wide temperature. The map reveals some interesting patterns – certain areas of the city in red are hotter than others. Since climate and weather don’t vary much over short distances, the temperature anomalies we see across the city are due to differences in the landscape, such as the amount of tree cover or development.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256932,"id":2256932,"title":"CCI_2_WithLegend_v2","filename":"CCI_2_WithLegend_v2.png","filesize":764588,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_2_withlegend_v2","alt":"A map of the afternoon temperature anomaly in Washington, D. C.","author":"10232","description":"","caption":"","name":"cci_2_withlegend_v2","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 23:47:37","modified":"2024-02-26 23:49:14","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":1052,"height":898,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","medium-width":306,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","medium_large-width":768,"medium_large-height":656,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","large-width":1052,"large-height":898,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","1536x1536-width":1052,"1536x1536-height":898,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","2048x2048-width":1052,"2048x2048-height":898,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2-545x465.png","card_image-width":545,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_2_WithLegend_v2.png","wide_image-width":1052,"wide_image-height":898}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

But this map only tells us about the physical phenomena. If we want to understand who is most at risk of extreme heat events, we need to create a map that brings together variables about temperature with variables about the population at risk.<\/p>\n

In Perform Analysis<\/a>, open the Calculate Composite Index<\/strong> tool, which you can find in Analyze patterns<\/strong>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256592,"id":2256592,"title":"CCI_3","filename":"CCI_3.png","filesize":13604,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_3","alt":"The Calculate Composite Index tool in Tools in Map Viewer","author":"10232","description":"","caption":"","name":"cci_3","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:45:18","modified":"2024-02-26 22:45:39","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":362,"height":381,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","medium-width":248,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","medium_large-width":362,"medium_large-height":381,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","large-width":362,"large-height":381,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","1536x1536-width":362,"1536x1536-height":381,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","2048x2048-width":362,"2048x2048-height":381,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","card_image-width":362,"card_image-height":381,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_3.png","wide_image-width":362,"wide_image-height":381}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Inside the tool, load the urban heat islands layer as the Input features or table<\/strong>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256602,"id":2256602,"title":"CCI_4","filename":"CCI_4.png","filesize":7839,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_4","alt":"Inputs in Calculate Composite Index","author":"10232","description":"","caption":"","name":"cci_4","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:46:00","modified":"2024-02-26 22:46:12","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":361,"height":155,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4-213x155.png","thumbnail-width":213,"thumbnail-height":155,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","medium-width":361,"medium-height":155,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","medium_large-width":361,"medium_large-height":155,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","large-width":361,"large-height":155,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","1536x1536-width":361,"1536x1536-height":155,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","2048x2048-width":361,"2048x2048-height":155,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","card_image-width":361,"card_image-height":155,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_4.png","wide_image-width":361,"wide_image-height":155}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

In Input variables<\/strong>, select the following three variables – one that indicates exposure to heat, and two that indicate vulnerability to heat:<\/p>\n

    \n
  1. Afternoon Temp Anomaly, with a Weight of 2. We\u2019ve made the weight of this variable two times more important than the others because it\u2019s a critical factor in determining the risk of high heat events.<\/li>\n
  2. Poverty %, with a Weight of 1<\/li>\n
  3. 65 and older %, with a Weight of 1<\/li>\n<\/ol>\n"},{"acf_fc_layout":"sidebar","content":"

    Note:<\/strong> this index is an illustrative example to demonstrate the capabilities of the tool. Some of the decisions being made here, like the variables and weights chosen, may have the potential to be refined further. Additionally, the author is not an expert on extreme heat events or the urban heat island effect.<\/p>\n

    This leads us to an important note of caution. Creating an index is simple. Creating an appropriate<\/em> index is a subjective and challenging process. It requires careful consideration of the question the index is trying to answer, variable choice, and the methods applied.\u00a0 The Creating Composite Indices Using ArcGIS: Best Practices<\/a> technical paper outlines the entire workflow of creating an appropriate composite index. Consider the best practices mentioned in this technical paper when designing and creating your own index, and be sure to work in consultation with domain experts and end users.<\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Center","spotlight_image":false},{"acf_fc_layout":"image","image":{"ID":2256672,"id":2256672,"title":"CCI_5","filename":"CCI_5.png","filesize":15503,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_5","alt":"Input variables in Calculate Composite Index","author":"10232","description":"","caption":"","name":"cci_5","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:54:30","modified":"2024-02-26 22:54:53","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":359,"height":664,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","medium-width":141,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","medium_large-width":359,"medium_large-height":664,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","large-width":359,"large-height":664,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","1536x1536-width":359,"1536x1536-height":664,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","2048x2048-width":359,"2048x2048-height":664,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5-251x465.png","card_image-width":251,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_5.png","wide_image-width":359,"wide_image-height":664}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    In Index settings<\/strong>, change the Minimum to 0 and the Maximum to 100. This means the output will be rescaled to make the minimum value be 0 and the maximum value be 100, so it is more interpretable. We\u2019ll use the defaults for the rest of the parameters.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256682,"id":2256682,"title":"CCI_6","filename":"CCI_6.png","filesize":13464,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_6","alt":"Index settings in Calculate Composite Index","author":"10232","description":"","caption":"","name":"cci_6","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:54:34","modified":"2024-02-26 22:55:12","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":359,"height":272,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","medium-width":344,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","medium_large-width":359,"medium_large-height":272,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","large-width":359,"large-height":272,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","1536x1536-width":359,"1536x1536-height":272,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","2048x2048-width":359,"2048x2048-height":272,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","card_image-width":359,"card_image-height":272,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_6.png","wide_image-width":359,"wide_image-height":272}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    Set the Output name<\/strong> to any name of your choice.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256692,"id":2256692,"title":"CCI_7","filename":"CCI_7.png","filesize":5343,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_7","alt":"Result layer in Calculate Composite Index","author":"10232","description":"","caption":"","name":"cci_7","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:54:37","modified":"2024-02-26 22:55:24","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":365,"height":121,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7-213x121.png","thumbnail-width":213,"thumbnail-height":121,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","medium-width":365,"medium-height":121,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","medium_large-width":365,"medium_large-height":121,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","large-width":365,"large-height":121,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","1536x1536-width":365,"1536x1536-height":121,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","2048x2048-width":365,"2048x2048-height":121,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","card_image-width":365,"card_image-height":121,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_7.png","wide_image-width":365,"wide_image-height":121}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    In Environment settings<\/strong>, set the Processing extent<\/strong> as Display extent<\/strong>. Make sure all of the Washington D.C. area census tracts show in your map extent.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256702,"id":2256702,"title":"CCI_8","filename":"CCI_8.png","filesize":13142,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_8","alt":"Environment settings in Calculate Composite Index","author":"10232","description":"","caption":"","name":"cci_8","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:54:40","modified":"2024-02-26 22:55:34","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":359,"height":252,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","medium-width":359,"medium-height":252,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","medium_large-width":359,"medium_large-height":252,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","large-width":359,"large-height":252,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","1536x1536-width":359,"1536x1536-height":252,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","2048x2048-width":359,"2048x2048-height":252,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","card_image-width":359,"card_image-height":252,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_8.png","wide_image-width":359,"wide_image-height":252}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    The results show us the darkest purple color in places where the afternoon temperature anomaly is higher, and<\/em> where a higher percentage of people are in poverty and a higher percentage of people are over 65+.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256942,"id":2256942,"title":"CCI_9_WithLegend_v2","filename":"CCI_9_WithLegend_v2.png","filesize":504047,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_9_withlegend_v2","alt":"","author":"10232","description":"","caption":"","name":"cci_9_withlegend_v2","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 23:50:14","modified":"2024-02-26 23:50:22","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":1052,"height":899,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","medium-width":305,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","medium_large-width":768,"medium_large-height":656,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","large-width":1052,"large-height":899,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","1536x1536-width":1052,"1536x1536-height":899,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","2048x2048-width":1052,"2048x2048-height":899,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2-544x465.png","card_image-width":544,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_9_WithLegend_v2.png","wide_image-width":1052,"wide_image-height":899}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    These are areas where, during an extreme heat event, the adverse impacts might be felt the greatest. Local government could use this map to help them prioritize where to add new cooling centers.<\/p>\n

    We can run the results of the Calculate Composite Index tool through the Find Outliers tool<\/a> to gain insights into the spatial patterns of the results. Use the Index \u2013 Mean field as the Analysis field<\/strong> then use defaults for the other parameters.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2256752,"id":2256752,"title":"CCI_10","filename":"CCI_10.png","filesize":17879,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/announcements\/introducing-the-calculate-composite-index-tool-in-arcgis-online-map-viewer\/cci_10","alt":"Find Outliers tool","author":"10232","description":"","caption":"","name":"cci_10","status":"inherit","uploaded_to":2246572,"date":"2024-02-26 22:59:59","modified":"2024-02-26 23:00:34","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":366,"height":479,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","medium-width":199,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","medium_large-width":366,"medium_large-height":479,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","large-width":366,"large-height":479,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","1536x1536-width":366,"1536x1536-height":479,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","2048x2048-width":366,"2048x2048-height":479,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10-355x465.png","card_image-width":355,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2024\/02\/CCI_10.png","wide_image-width":366,"wide_image-height":479}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

    The output of this tool shows us different types of clusters and outliers in the index:<\/p>\n