{"id":1866732,"date":"2023-03-13T10:48:46","date_gmt":"2023-03-13T17:48:46","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1866732"},"modified":"2023-06-15T09:59:15","modified_gmt":"2023-06-15T16:59:15","slug":"new-calculate-composite-index-tool-in-arcgis-pro-3-1","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1","title":{"rendered":"Explore the New Calculate Composite Index Tool in ArcGIS Pro 3.1"},"author":334612,"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],"tags":[769372,25581],"industry":[],"product":[36561],"class_list":["post-1866732","blog","type-blog","status-publish","format-standard","hentry","category-analytics","tag-composite-index","tag-spatial-statistics","product-arcgis-pro"],"acf":{"authors":[{"ID":334612,"user_firstname":"Catherine","user_lastname":"McSorley","nickname":"Catherine McSorley","user_nicename":"cmcsorley","display_name":"Catherine McSorley","user_email":"cmcsorley@esri.com","user_url":"","user_registered":"2023-03-06 19:01:15","user_description":"Catherine McSorley is a Product Engineer on the Spatial Statistics Team at Esri.","user_avatar":""}],"short_description":"Create indices measuring risk, equity, vulnerability, and more, using the new Calculate Composite Index tool.","flexible_content":[{"acf_fc_layout":"content","content":"

With the release of ArcGIS Pro 3.1, you now have access to a new tool in the Spatial Statistics toolbox<\/span>: Calculate Composite Index<\/a>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866752,"id":1866752,"title":"","filename":"CCI_tool.png","filesize":108466,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/cci_tool","alt":"Screenshot of the Calculate Composite Index tool in ArcGIS Pro","author":"334612","description":"","caption":"","name":"cci_tool","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:14:56","modified":"2023-03-06 19:15:18","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":486,"height":870,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","medium-width":146,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","medium_large-width":486,"medium_large-height":870,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","large-width":486,"large-height":870,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","1536x1536-width":486,"1536x1536-height":870,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","2048x2048-width":486,"2048x2048-height":870,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool-260x465.png","card_image-width":260,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/CCI_tool.png","wide_image-width":486,"wide_image-height":870}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

What is an Index?<\/h3>\n"},{"acf_fc_layout":"content","content":"

Composite indices are commonly used across social research, epidemiology, government programs, and more, to measure complex phenomena using a single indicator. The new Calculate Composite Index tool provides a workflow and guidance to help generate these indices.<\/p>\n"},{"acf_fc_layout":"content","content":"

Case Study – Mapping Severe Influenza Risk<\/h1>\n"},{"acf_fc_layout":"content","content":"

Data Source<\/a><\/p>\n"},{"acf_fc_layout":"content","content":"

Understanding the problem and choosing variables<\/h3>\n"},{"acf_fc_layout":"content","content":"

Suppose a group of public health analysts want to target their flu season health campaigns at a more local level by understanding what areas of the country are most at-risk for severe cases of influenza.<\/p>\n

There is no single measurable variable that can tell the analysts here are the places where people are most at-risk<\/em>. Being at-risk for severe cases of influenza comes from multiple attributes that each are measurable on their own and can be combined to measure the larger theme of Severe Influenza Risk<\/em>. The new Calculate Composite Index tool can help achieve this goal.<\/p>\n

One way to break up the influenza risk problem is into two parts – Risk factors<\/em>\u00a0and Vaccination status<\/em>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1873462,"id":1873462,"title":"","filename":"flu-flow-2.png","filesize":45531,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/flu-flow-2","alt":"a flow chart showing how flu risk can be broken up into risk factors and vaccination","author":"334612","description":"","caption":"","name":"flu-flow-2","status":"inherit","uploaded_to":1866732,"date":"2023-03-13 17:38:43","modified":"2023-03-13 17:39:06","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":630,"height":402,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","medium-width":409,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","medium_large-width":630,"medium_large-height":402,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","large-width":630,"large-height":402,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","1536x1536-width":630,"1536x1536-height":402,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","2048x2048-width":630,"2048x2048-height":402,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","card_image-width":630,"card_image-height":402,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu-flow-2.png","wide_image-width":630,"wide_image-height":402}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Risk factors can be further broken up into % of people over 65<\/em>, and % of people reporting poor\/fair health<\/em>. Vaccination Status can be directly measured by % of people receiving a flu vaccination<\/em>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866772,"id":1866772,"title":"","filename":"pct_65plus.png","filesize":193852,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/pct_65plus","alt":"Map of the contiguous U.S. showing the percent of people over 65 in each county","author":"334612","description":"","caption":"","name":"pct_65plus","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:20:44","modified":"2023-03-06 19:21:13","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":630,"height":409,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","medium-width":402,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","medium_large-width":630,"medium_large-height":409,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","large-width":630,"large-height":409,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","1536x1536-width":630,"1536x1536-height":409,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","2048x2048-width":630,"2048x2048-height":409,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","card_image-width":630,"card_image-height":409,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_65plus.png","wide_image-width":630,"wide_image-height":409}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":1866782,"id":1866782,"title":"","filename":"pct_poorhealth.png","filesize":334057,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/pct_poorhealth","alt":"Map of the contiguous U.S. showing the percent of people reporting poor or fair health in each county","author":"334612","description":"","caption":"","name":"pct_poorhealth","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:21:28","modified":"2023-03-06 19:21:58","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":630,"height":397,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","medium-width":414,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","medium_large-width":630,"medium_large-height":397,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","large-width":630,"large-height":397,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","1536x1536-width":630,"1536x1536-height":397,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","2048x2048-width":630,"2048x2048-height":397,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","card_image-width":630,"card_image-height":397,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_poorhealth.png","wide_image-width":630,"wide_image-height":397}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"image","image":{"ID":1866792,"id":1866792,"title":"","filename":"pct_vax.png","filesize":349611,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/pct_vax","alt":"A map of the contiguous U.S. showing the percent of people that receive a flu vaccination in each county","author":"334612","description":"","caption":"","name":"pct_vax","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:22:10","modified":"2023-03-06 19:22:36","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":630,"height":411,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","medium-width":400,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","medium_large-width":630,"medium_large-height":411,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","large-width":630,"large-height":411,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","1536x1536-width":630,"1536x1536-height":411,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","2048x2048-width":630,"2048x2048-height":411,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","card_image-width":630,"card_image-height":411,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/pct_vax.png","wide_image-width":630,"wide_image-height":411}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Each of these variables can be added as inputs to the Calculate Composite Index tool.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866802,"id":1866802,"title":"","filename":"input_variables.png","filesize":30917,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/input_variables","alt":"Screenshot of the Index tool showing the drop down to input variables","author":"334612","description":"","caption":"","name":"input_variables","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:23:00","modified":"2023-03-06 19:23:20","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":514,"height":212,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","medium-width":464,"medium-height":191,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","medium_large-width":514,"medium_large-height":212,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","large-width":514,"large-height":212,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","1536x1536-width":514,"1536x1536-height":212,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","2048x2048-width":514,"2048x2048-height":212,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","card_image-width":514,"card_image-height":212,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/input_variables.png","wide_image-width":514,"wide_image-height":212}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

When calculating an index, it\u2019s important to ensure that each of your variables are contributing to the phenomenon you\u2019re measuring in the same direction. In this case, as each of our variables increases, we would like for Severe Influenza Risk<\/em> to increase as well. For the Risk factors<\/em>\u00a0variables this is already true. As the % of People over 65 increases, so does risk. However, for the vaccination variable, we see the opposite effect. As the % of People vaccinated for influenza increases, risk decreases. To flip this relationship, we can check the Reverse Direction<\/em>\u00a0box next to the vaccination variable. This reverses the relationship, so as the % of People vaccinated for the flu decreases, risk will increase.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866812,"id":1866812,"title":"reverse_direction","filename":"reverse_direction.png","filesize":7437,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/reverse_direction","alt":"Screenshot of the index tool showing the Reverse Direction checkbox","author":"334612","description":"","caption":"","name":"reverse_direction","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:23:43","modified":"2023-03-06 19:24:34","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":457,"height":184,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction-213x184.png","thumbnail-width":213,"thumbnail-height":184,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","medium-width":457,"medium-height":184,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","medium_large-width":457,"medium_large-height":184,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","large-width":457,"large-height":184,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","1536x1536-width":457,"1536x1536-height":184,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","2048x2048-width":457,"2048x2048-height":184,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","card_image-width":457,"card_image-height":184,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/reverse_direction.png","wide_image-width":457,"wide_image-height":184}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Though each of the variables are represented as percentages, their ranges differ. When combining variables that are not in the same units or range, there are several ways to preprocess<\/em> the variables before combining. A simple way to preprocess the variables is through a method called min-max scaling. This method transforms each variable so its minimum value is equal to 0 and its maximum value is equal to 1. Min-max scaling does not change the shape of the distribution, so if the distribution is skewed or has an outlier to begin with, it will also be skewed after scaling.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866832,"id":1866832,"title":"minmax","filename":"minmax.png","filesize":20062,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/minmax","alt":"A graphic showing the before and after of minmax preprocessing","author":"334612","description":"","caption":"","name":"minmax","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:24:59","modified":"2023-03-06 19:25:18","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":630,"height":189,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax-213x189.png","thumbnail-width":213,"thumbnail-height":189,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","medium-width":464,"medium-height":139,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","medium_large-width":630,"medium_large-height":189,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","large-width":630,"large-height":189,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","1536x1536-width":630,"1536x1536-height":189,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","2048x2048-width":630,"2048x2048-height":189,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","card_image-width":630,"card_image-height":189,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/minmax.png","wide_image-width":630,"wide_image-height":189}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Once variables are preprocessed, they must be combined using a mathematical operation such as sum or multiplication. The preset methods in the tool can be used to specify a preprocessing method and a combination method. The first preset in the tool – Combine values (mean of scaled values)<\/em> – applies min-max scaling to preprocess, then mean to combine.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866842,"id":1866842,"title":"preset_methods","filename":"preset_methods.png","filesize":38013,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/preset_methods","alt":"A screenshot of the Index tool showing the preset combination method","author":"334612","description":"","caption":"","name":"preset_methods","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:25:41","modified":"2023-03-06 19:25:56","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":508,"height":176,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods-213x176.png","thumbnail-width":213,"thumbnail-height":176,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","medium-width":464,"medium-height":161,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","medium_large-width":508,"medium_large-height":176,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","large-width":508,"large-height":176,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","1536x1536-width":508,"1536x1536-height":176,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","2048x2048-width":508,"2048x2048-height":176,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","card_image-width":508,"card_image-height":176,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/preset_methods.png","wide_image-width":508,"wide_image-height":176}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Output Settings<\/h3>\n"},{"acf_fc_layout":"content","content":"

To further customize the index output, a custom name can be specified, such as Severe Influenza Risk<\/em>. Additional outputs can also be specified – these postprocess<\/em> the output index to make the results more interpretable.<\/span> In this case, if the analysts are interested in understanding what counties might have much<\/em> higher than average risk<\/em>\u00a0the Standard deviation class could be selected as additional output, since standard deviations are measured in relation to the average.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866862,"id":1866862,"title":"","filename":"output_settings.png","filesize":13366,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/output_settings","alt":"Screenshot of the index tool showing the output settings, including the check box for Standard deviation selected.","author":"334612","description":"","caption":"","name":"output_settings","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:27:14","modified":"2023-03-06 19:27:38","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":499,"height":402,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","medium-width":324,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","medium_large-width":499,"medium_large-height":402,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","large-width":499,"large-height":402,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","1536x1536-width":499,"1536x1536-height":402,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","2048x2048-width":499,"2048x2048-height":402,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","card_image-width":499,"card_image-height":402,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/output_settings.png","wide_image-width":499,"wide_image-height":402}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Once all the settings have been specified, the tool can be run.<\/p>\n"},{"acf_fc_layout":"content","content":"

Results and Interpretation<\/h3>\n"},{"acf_fc_layout":"content","content":"

The Calculate Composite Index tool outputs the Severe Influenza Risk Index as an average of each of the preprocessed variables. Counties in purple have higher risk, and counties in light blue \/ white have lower risk.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866922,"id":1866922,"title":"","filename":"flu_risk_index-1.png","filesize":313238,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/flu_risk_index-2","alt":"Map of the contiguous U.S. showing the raw flu risk Index as a mean of the preprocessed inputs","author":"334612","description":"","caption":"","name":"flu_risk_index-2","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:34:35","modified":"2023-03-06 19:35:04","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":630,"height":407,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","medium-width":404,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","medium_large-width":630,"medium_large-height":407,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","large-width":630,"large-height":407,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","1536x1536-width":630,"1536x1536-height":407,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","2048x2048-width":630,"2048x2048-height":407,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","card_image-width":630,"card_image-height":407,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_index-1.png","wide_image-width":630,"wide_image-height":407}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

The second output is the Standard Deviation classes. The darker purple areas can tell us which areas have risk much higher than average since their values are at least one standard deviation above the mean. Public health analysts could prioritize the purple areas for their influenza vaccination and education campaigns.<\/span><\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866902,"id":1866902,"title":"","filename":"flu_risk_stdev.png","filesize":299425,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/flu_risk_stdev","alt":"Map of the contiguous U.S. showing severe influenza risk in standard deviation classes.","author":"334612","description":"","caption":"","name":"flu_risk_stdev","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:33:36","modified":"2023-03-06 19:34:03","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":630,"height":405,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","medium-width":406,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","medium_large-width":630,"medium_large-height":405,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","large-width":630,"large-height":405,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","1536x1536-width":630,"1536x1536-height":405,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","2048x2048-width":630,"2048x2048-height":405,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","card_image-width":630,"card_image-height":405,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_stdev.png","wide_image-width":630,"wide_image-height":405}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Investigating an individual feature\u2019s results can help reveal more about what leads to a higher or lower risk index value. The feature below in New Mexico appears as dark purple in the standard deviation classes map.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1867332,"id":1867332,"title":"","filename":"nm.png","filesize":207429,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/nm","alt":"Map that shows the county in New Mexico that will be chosen for the pop-up","author":"334612","description":"","caption":"","name":"nm","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 21:58:22","modified":"2023-03-06 21:58:45","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":630,"height":289,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","medium-width":464,"medium-height":213,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","medium_large-width":630,"medium_large-height":289,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","large-width":630,"large-height":289,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","1536x1536-width":630,"1536x1536-height":289,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","2048x2048-width":630,"2048x2048-height":289,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","card_image-width":630,"card_image-height":289,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/nm.png","wide_image-width":630,"wide_image-height":289}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

In the pop-up, you can see the variables\u2019 original values, as well as their preprocessed values. While, in this county, there is not a particularly high percent of people reporting poor health (the min-max value is ~0.3 in a possible range of 0 to 1), the percent of people over 65 is relatively high, and the percent of people receiving flu vaccinations is relatively low. The variables driving this county\u2019s risk to be over three standard deviations higher than the average are the age of its citizens and the low vaccination rates.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866932,"id":1866932,"title":"","filename":"flu_risk_casestudy.png","filesize":137351,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/flu_risk_casestudy","alt":"A pop-up showing the original inputs and preprocessed inputs for a selected feature.","author":"334612","description":"","caption":"","name":"flu_risk_casestudy","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:35:36","modified":"2023-03-06 19:35:59","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":630,"height":479,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","medium-width":343,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","medium_large-width":630,"medium_large-height":479,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","large-width":630,"large-height":479,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","1536x1536-width":630,"1536x1536-height":479,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","2048x2048-width":630,"2048x2048-height":479,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy-612x465.png","card_image-width":612,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/flu_risk_casestudy.png","wide_image-width":630,"wide_image-height":479}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

The tool also creates several useful charts<\/a>, including the distribution of the index, the distributions of the input variables, and the relationships and correlations between variables.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":1866942,"id":1866942,"title":"","filename":"index_distribution.png","filesize":40670,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\/index_distribution","alt":"A histogram showing the distribution of the index","author":"334612","description":"","caption":"","name":"index_distribution","status":"inherit","uploaded_to":1866732,"date":"2023-03-06 19:36:24","modified":"2023-03-06 19:36:41","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":630,"height":243,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","medium-width":464,"medium-height":179,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","medium_large-width":630,"medium_large-height":243,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","large-width":630,"large-height":243,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","1536x1536-width":630,"1536x1536-height":243,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","2048x2048-width":630,"2048x2048-height":243,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","card_image-width":630,"card_image-height":243,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2023\/03\/index_distribution.png","wide_image-width":630,"wide_image-height":243}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Conclusion<\/h1>\n"},{"acf_fc_layout":"content","content":"

The Calculate Composite Index tool can help researchers, policy makers, and analysts create an index to quantify immeasurable phenomena by combining together the measurable components of the problem.<\/span> See the links below to learn more about how the Calculate Composite Index tool works, and best practices when creating a composite index.<\/p>\n"},{"acf_fc_layout":"content","content":"

Resources<\/h1>\n"},{"acf_fc_layout":"content","content":"

Calculate Composite Index Documentation<\/a><\/p>\n

How Calculate Composite Index Works<\/a><\/p>\n

Calculate Composite Index Best Practices Technical Paper<\/a><\/p>\n

Organisation for Economic Co-operation and Development Handbook on Constructing Composite Indicators: Methodology and User Guide<\/a><\/p>\n

 <\/p>\n"}],"related_articles":[{"ID":1620162,"post_author":"58381","post_date":"2022-07-06 10:00:42","post_date_gmt":"2022-07-06 17:00:42","post_content":"","post_title":"Discovering spatial relationships with Multiscale Geographically Weighted Regression","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"discovering-spatial-relationships-with-multiscale-geographically-weighted-regression","to_ping":"","pinged":"","post_modified":"2022-07-06 13:09:51","post_modified_gmt":"2022-07-06 20:09:51","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1620162","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":1235582,"post_author":"10232","post_date":"2021-05-20 09:38:34","post_date_gmt":"2021-05-20 16:38:34","post_content":"","post_title":"Introducing Data Engineering in ArcGIS Pro","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"introducing-data-engineering-in-arcgis-pro","to_ping":"","pinged":"","post_modified":"2022-03-30 15:09:05","post_modified_gmt":"2022-03-30 22:09:05","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=1235582","menu_order":0,"post_type":"blog","post_mime_type":"","comment_count":"1","filter":"raw"},{"ID":1603512,"post_author":"71281","post_date":"2022-06-16 14:54:23","post_date_gmt":"2022-06-16 21:54:23","post_content":"","post_title":"What\u2019s new in Forest-based Forecast","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"whats-new-in-forest-based-forecast","to_ping":"","pinged":"","post_modified":"2022-06-23 15:35:02","post_modified_gmt":"2022-06-23 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\/>\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=\"2023-06-15T16:59:15+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@ESRI\" \/>\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-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/analytics\/new-calculate-composite-index-tool-in-arcgis-pro-3-1\"},\"author\":{\"name\":\"Catherine McSorley\",\"@id\":\"https:\/\/www.esri.com\/arcgis-blog\/#\/schema\/person\/29517736b3d6833282d8e385f04d6a40\"},\"headline\":\"Explore the New Calculate 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