{"id":895271,"date":"2020-11-12T10:23:08","date_gmt":"2020-11-12T18:23:08","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=895271"},"modified":"2021-08-03T00:20:41","modified_gmt":"2021-08-03T07:20:41","slug":"mapping-large-datasets-part-2","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/mapping\/mapping-large-datasets-part-2","title":{"rendered":"Out of bounds: Mapping large datasets in ArcGIS Insights, part 2"},"author":6771,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[22941],"tags":[25361,659331,34711],"industry":[],"product":[36801],"class_list":["post-895271","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-binning","tag-heat-maps","tag-points","product-insights"],"acf":{"short_description":"Binned maps and heat maps can help you understand the spatial distribution of your large datasets.","flexible_content":[{"acf_fc_layout":"content","content":"

In the last blog<\/a>, we discussed why it can be difficult to interpret patterns in large dataset on a location map and how to use spatial aggregation and graduated symbols maps to understand your data. In this blog, we will look at two different map types: binned maps and heat maps.<\/p>\n"},{"acf_fc_layout":"sidebar","content":"

Binned maps and heat maps are both quick ways to visualize your point data. The bins and densities are created for display only and do not alter your original dataset. Your point features will still be used in all analytical processes.<\/p>\n","image_reference":false,"layout":"standard","image_reference_figure":"","snippet":"","spotlight_name":"","section_title":"","position":"Right","spotlight_image":false},{"acf_fc_layout":"content","content":"

Binned maps<\/h2>\n

In some cases, the counts across the study area are important, but the comparison between standard boundaries, like we saw using spatial aggregation, is not. A binned map displays the counts of points in a uniform grid across the entire study area, which helps you understand the distribution of your spatial data<\/a>, often at a more acute scale than with a graduated symbols map. The resolution of the binned map can be changed to increase or decrease the size of the bins, and the cell size will change as you zoom in and out on the map.<\/p>\n

In the case of the wildfires, the binned map is a higher resolution visualization than the graduated symbols map, which allows us to analyze the distribution of fires without boundaries. We can see that the areas with the most wildfires still correspond to the states with the most wildfires in the graduated symbols map, but the binned map provides a more granular view of the areas in the states in which the wildfires are occurring.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":895311,"id":895311,"title":"binned_map","filename":"binned_map.png","filesize":58149,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/mapping\/mapping-large-datasets-part-2\/binned_map","alt":"Binned map of wildfires","author":"6771","description":"","caption":"","name":"binned_map","status":"inherit","uploaded_to":895271,"date":"2020-06-22 15:17:11","modified":"2020-06-22 15:17:31","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":1121,"height":445,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","medium-width":464,"medium-height":184,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","medium_large-width":768,"medium_large-height":305,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","large-width":1121,"large-height":445,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","1536x1536-width":1121,"1536x1536-height":445,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","2048x2048-width":1121,"2048x2048-height":445,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map-826x328.png","card_image-width":826,"card_image-height":328,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/binned_map.png","wide_image-width":1121,"wide_image-height":445}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Zooming in on the map automatically displays the data at a higher resolution. If you zoom in far enough, the bins will be replaced with raw data points.<\/p>\n

The map below is zoomed in on Texas and surrounding areas.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":895331,"id":895331,"title":"bins_texas","filename":"bins_texas.png","filesize":22217,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/insights\/mapping\/mapping-large-datasets-part-2\/bins_texas","alt":"Binned map of wild fires, zoomed in to Texas","author":"6771","description":"","caption":"","name":"bins_texas","status":"inherit","uploaded_to":895271,"date":"2020-06-22 15:17:45","modified":"2020-06-22 15:18:03","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":765,"height":443,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","medium-width":451,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","medium_large-width":765,"medium_large-height":443,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","large-width":765,"large-height":443,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","1536x1536-width":765,"1536x1536-height":443,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","2048x2048-width":765,"2048x2048-height":443,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","card_image-width":765,"card_image-height":443,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2020\/06\/bins_texas.png","wide_image-width":765,"wide_image-height":443}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

When should you use a binned map?<\/p>\n