{"id":2975697,"date":"2026-07-08T11:01:01","date_gmt":"2026-07-08T18:01:01","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2975697"},"modified":"2026-07-09T09:37:37","modified_gmt":"2026-07-09T16:37:37","slug":"global-biodiversity-and-conservation-hexagons-but-better","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/sustainable-development\/global-biodiversity-and-conservation-hexagons-but-better","title":{"rendered":"Global Biodiversity and Conservation Hexagons&#8230;but better!"},"author":7841,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"open","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[430212],"tags":[741031,43821,268131],"industry":[],"product":[36581],"class_list":["post-2975697","blog","type-blog","status-publish","format-standard","hentry","category-sustainable-development","tag-biodiversity","tag-conservation","tag-living-atlas","product-arcgis-living-atlas"],"acf":{"authors":[{"ID":7841,"user_firstname":"Dan","user_lastname":"Pisut","nickname":"Dan Pisut","user_nicename":"dan-pisut","display_name":"Dan Pisut","user_email":"DPisut@esri.com","user_url":"https:\/\/livingatlas.arcgis.com","user_registered":"2018-04-16 21:24:57","user_description":"Dan leads development of ArcGIS Living Atlas environmental content, which includes information about Earth's land, ocean, atmosphere, climate, and ecosystems. Prior to Esri, Dan worked at NOAA for two decades, leading data visualization efforts for research, communications, and education.","user_avatar":"<img data-del=\"avatar\" src='https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/Dan-Pisut-headshot-465x465.jpg' class='avatar pp-user-avatar avatar-96 photo ' height='96' width='96'\/>"}],"short_description":"Updates to the Global Biodiversity and Conservation Hexagons in Living Atlas improve the accuracy and functionality of this resource.","flexible_content":[{"acf_fc_layout":"content","content":"<p>Over the past year since the beta version of the Global Hexagons for Biodiversity and Conservation was released, we\u2019ve heard amazing stories of the GIS community leveraging this resource to report on conservation targets and plan for the future. For example, a common workflow would include filtering areas for high biodiversity or threatened species, then excluding those hexagons if they\u2019re currently protected, and then looking at the types of ecosystems or land use characteristics of the remaining hexagons to align with 30&#215;30 goals.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2975702,"id":2975702,"title":"speciesrichness","filename":"speciesrichness.png","filesize":156787,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/sustainable-development\/global-biodiversity-and-conservation-hexagons-but-better\/speciesrichness","alt":"Species richness","author":"7841","description":"","caption":"A single variable map showing species richness using IUCN Red List data.","name":"speciesrichness","status":"inherit","uploaded_to":2975697,"date":"2026-07-08 16:47:49","modified":"2026-07-08 17:02:41","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":1138,"height":400,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","medium-width":464,"medium-height":163,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","medium_large-width":768,"medium_large-height":270,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","large-width":1138,"large-height":400,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","1536x1536-width":1138,"1536x1536-height":400,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","2048x2048-width":1138,"2048x2048-height":400,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness-826x290.png","card_image-width":826,"card_image-height":290,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png","wide_image-width":1138,"wide_image-height":400}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness.png"},{"acf_fc_layout":"content","content":"<p>Using the Global Hexagons for Biodiversity and Conservation means that this work can be done in minutes rather than days. We are continuing to support this process and now have an improved version of the <a href=\"https:\/\/www.arcgis.com\/home\/item.html?id=8e1e15e336024f01894a6253bbf756d7\">Global Hexagons for Biodiversity and Conservation<\/a>.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2975700,"id":2975700,"title":"oceanconservation","filename":"oceanconservation.png","filesize":267703,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/sustainable-development\/global-biodiversity-and-conservation-hexagons-but-better\/oceanconservation","alt":"Bivariate map of ocean conservation","author":"7841","description":"","caption":"Bivariate map combines areas that are already protected with areas with a high priority for protection.","name":"oceanconservation","status":"inherit","uploaded_to":2975697,"date":"2026-07-08 16:47:45","modified":"2026-07-08 16:50:05","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":1538,"height":908,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","medium-width":442,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","medium_large-width":768,"medium_large-height":453,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","large-width":1538,"large-height":908,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation-1536x907.png","1536x1536-width":1536,"1536x1536-height":907,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","2048x2048-width":1538,"2048x2048-height":908,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation-788x465.png","card_image-width":788,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png","wide_image-width":1538,"wide_image-height":908}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/oceanconservation.png"},{"acf_fc_layout":"content","content":"<h3><strong>What has changed?<\/strong><\/h3>\n<ul>\n<li>Updated data, where available. Also, the ESA WorldCover land cover product was removed since the data was not being updated by the source. All land cover is based on the Esri Sentinel-2 10m Land Use Land Cover product.<\/li>\n<li>All units have been harmonized across datasets and statistics. For example, all linear and aerial units are in meters rather than a mix of kilometers and meters. Bivariate or composite index maps that combine aerial measures are now more easily comparable.<\/li>\n<li>Implemented a new methodology for spatially summarizing partial pixel data that falls within a hexagon, which should result in capturing more extreme values in the minimum and maximum statistics. Applying a weighted value of that partial pixel also improves the accuracy of mean and predominant statistics.<\/li>\n<li>Additional statistics for some datasets, including precalculated percentages. There are now <strong>82 summary statistics<\/strong>.<\/li>\n<li>More meaningful field aliases and long field descriptions.<\/li>\n<li>Data architecture that relies on 1 layer with sublayers rather than a group layer.<\/li>\n<\/ul>\n"},{"acf_fc_layout":"image","image":{"ID":2975699,"id":2975699,"title":"rankindex","filename":"rankindex.png","filesize":287348,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-living-atlas\/sustainable-development\/global-biodiversity-and-conservation-hexagons-but-better\/rankindex","alt":"Composite index of conservation priority","author":"7841","description":"","caption":"Using the Create Composite Index tool, multiple variables were combined to create a single layer that ranks areas in need of conservation.","name":"rankindex","status":"inherit","uploaded_to":2975697,"date":"2026-07-08 16:47:40","modified":"2026-07-08 16:51:26","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":1602,"height":723,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","medium-width":464,"medium-height":209,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","medium_large-width":768,"medium_large-height":347,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","large-width":1602,"large-height":723,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex-1536x693.png","1536x1536-width":1536,"1536x1536-height":693,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","2048x2048-width":1602,"2048x2048-height":723,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex-826x373.png","card_image-width":826,"card_image-height":373,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png","wide_image-width":1602,"wide_image-height":723}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/rankindex.png"},{"acf_fc_layout":"content","content":"<h3><strong>Using the Global Hexagons for Biodiversity and Conservation<\/strong><\/h3>\n<p>Besides the workflow mentioned above, there are so many ways to analyze or visualize the data within the Hexagons, such as<\/p>\n<ul>\n<li>Create\u00a0<a href=\"https:\/\/learn.arcgis.com\/en\/paths\/multivariate-maps-what-they-are-and-how-to-make-them\/\">multivariate maps<\/a><\/li>\n<li>Use one variable to filter or apply\u00a0<a href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-online\/mapping\/feature-specific-effects\">feature-specific effects<\/a>\u00a0to emphasize another<\/li>\n<li><a href=\"https:\/\/pro.arcgis.com\/en\/pro-app\/latest\/tool-reference\/spatial-statistics\/calculate-composite-index.htm\">Calculate a Composite Index<\/a>\u00a0of multiple variables<\/li>\n<li>Use the\u00a0<a href=\"https:\/\/doc.arcgis.com\/en\/arcgis-online\/analyze\/find-similar-locations-mv.htm\">Find Similar<\/a>\u00a0tool<\/li>\n<li>Summarize your own data using\u00a0<a href=\"https:\/\/arcgis.com\/home\/item.html?id=5334817d9f6a41ae88ca6b4182fc07dc\">blank H3 hexagons<\/a>\u00a0and join the fields using the GRID ID\/Hexagon ID.<\/li>\n<\/ul>\n"}],"related_articles":[{"ID":2883592,"post_author":"7841","post_date":"2025-07-09 10:50:39","post_date_gmt":"2025-07-09 17:50:39","post_content":"","post_title":"Introducing Global Biodiversity and Conservation Hexagons","post_excerpt":"","post_status":"publish","comment_status":"open","ping_status":"closed","post_password":"","post_name":"biodiversity-conservation-hexagons","to_ping":"","pinged":"","post_modified":"2026-07-08 08:34:17","post_modified_gmt":"2026-07-08 15:34:17","post_content_filtered":"","post_parent":0,"guid":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&#038;p=2883592","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\/07\/speciesrichness-card.png","wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2026\/07\/speciesrichness-wide.png"},"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>Global Biodiversity and Conservation Hexagons...but better!<\/title>\n<meta name=\"description\" content=\"Access over 80 summary statistics from 28 key biodiversity and conservation datasets at multiple H3 hexagon resolutions.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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