{"id":2808372,"date":"2025-06-18T06:00:17","date_gmt":"2025-06-18T13:00:17","guid":{"rendered":"https:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=2808372"},"modified":"2025-07-02T05:47:11","modified_gmt":"2025-07-02T12:47:11","slug":"mapping-inaturalist-observations-with-map-viewer","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/mapping-inaturalist-observations-with-map-viewer","title":{"rendered":"Mapping iNaturalist observations with Map Viewer"},"author":129801,"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":[42641,26451,775612,40161,33371],"industry":[],"product":[36551,36611,380802],"class_list":["post-2808372","blog","type-blog","status-publish","format-standard","hentry","category-mapping","tag-arcgis-online","tag-cartography","tag-inaturalist","tag-living-atlas-of-the-world","tag-map-viewer","product-arcgis-online","product-story-maps","product-arcgis-storymaps"],"acf":{"authors":[{"ID":129801,"user_firstname":"Warren","user_lastname":"Davison","nickname":"Warren Davison","user_nicename":"wdavison","display_name":"Warren Davison","user_email":"wdavison@esri.com","user_url":"https:\/\/warrenrdavison.wixsite.com\/maps","user_registered":"2020-11-18 21:21:08","user_description":"I specialize in creating engaging maps and graphics that tell immersive, place-based stories. Based in Kitchener, Canada, I work with Esri\u2019s StoryMaps team, where I enjoy sharing the creative process behind each project. When I'm not exploring vectors and pixels, you\u2019ll likely find me cycling around town with my kids along for the ride.","user_avatar":""},{"ID":363212,"user_firstname":"Heidi","user_lastname":"Daulton","nickname":"Heidi Daulton","user_nicename":"hdaulton","display_name":"Heidi Daulton","user_email":"hdaulton@esri.com","user_url":"","user_registered":"2024-10-15 18:03:24","user_description":"Heidi Daulton is a senior project manager for Esri\u2019s StoryMaps team. Prior to joining Esri, Heidi worked across the conservation nonprofit space doing education, GIS, and communications. She's a big fan of ultrarunning, public libraries, and her chickens.","user_avatar":""}],"short_description":"Don't get bogged down in all the tips and tricks of wrangling iNaturalist observations to craft the maps in this story about carnivorous plants.","flexible_content":[{"acf_fc_layout":"content","content":"

Ever since the iNaturalist observations were made available in ArcGIS Living Atlas<\/a>, we’ve visualized the data countless times using Map Viewer to support our storytelling about the natural world. From prairie dogs<\/a> to coyotes and red foxes<\/a>, our projects frequently feature this dataset, partly due to our fascination with nature but also because of its incredible extent and richness.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2808402,"id":2808402,"title":"Blog_Intro_World_Map","filename":"Blog_Intro_World_Map.jpg","filesize":319259,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/mapping-inaturalist-observations-with-map-viewer\/blog_intro_world_map","alt":"A map of the world in the Natural Earth projection with a mesh of hexagons containing proportional circles scaled by the number of iNaturalist observations that occur within. These proportional symbols are color-coded according to the predominant taxon observed within each hexagon.","author":"129801","description":"","caption":"The iNaturalist datasets numbers millions of observations spanning nearly 500 species across the globe.","name":"blog_intro_world_map","status":"inherit","uploaded_to":2808372,"date":"2025-05-26 16:05:36","modified":"2025-05-26 17:38:34","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1893,"height":933,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","medium-width":464,"medium-height":229,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","medium_large-width":768,"medium_large-height":379,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","large-width":1893,"large-height":933,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map-1536x757.jpg","1536x1536-width":1536,"1536x1536-height":757,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","2048x2048-width":1893,"2048x2048-height":933,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map-826x407.jpg","card_image-width":826,"card_image-height":407,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Intro_World_Map.jpg","wide_image-width":1893,"wide_image-height":933}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

In Bog wild<\/em><\/a>, we use the iNaturalist observations to explore the wild world of bogs in North America and the incredible plants that call these habitats home. This blog outlines some of the tips and tricks we’ve learned along the way for working with the data in Map Viewer and weaving these biodiversity maps into the narrative of our stories.<\/p>\n"},{"acf_fc_layout":"content","content":"

Techniques<\/h1>\n

As mentioned, the iNaturalist observations are extensive. The dataset contains millions of observations spanning nearly 500 species, so effectively wrangling and visualizing this data is essential to the story.<\/p>\n

Filtering the data<\/h2>\n

The prepared layers in the Living Atlas<\/a> are great examples of how we can visualize the data at various scales using hexbins and the predominant size and category<\/a>. This style shows the total number of observations within each bin and the most frequently observed taxon.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2808412,"id":2808412,"title":"Blog_Annotated_Symbol_Pop-up","filename":"Blog_Annotated_Symbol_Pop-up.jpg","filesize":179428,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/mapping-inaturalist-observations-with-map-viewer\/blog_annotated_symbol_pop-up","alt":"A map of hexbins visualized with proportional symbols color-coded by the most predominant taxon observed within the area. One of the features has been clicked to reveal the pop-up containing a description of the number of iNaturalist observations found within the hexbin and a pie chart of the observed taxon.","author":"129801","description":"","caption":"The predominant size and category symbology quickly visualizes which taxon has been observed most frequently within the hexbin.","name":"blog_annotated_symbol_pop-up","status":"inherit","uploaded_to":2808372,"date":"2025-05-26 16:06:03","modified":"2025-05-26 17:49:04","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":1553,"height":932,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up-213x200.jpg","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","medium-width":435,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","medium_large-width":768,"medium_large-height":461,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","large-width":1553,"large-height":932,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up-1536x922.jpg","1536x1536-width":1536,"1536x1536-height":922,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","2048x2048-width":1553,"2048x2048-height":932,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up-775x465.jpg","card_image-width":775,"card_image-height":465,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Annotated_Symbol_Pop-up.jpg","wide_image-width":1553,"wide_image-height":932}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

While convenient, the Living Atlas layers’ aggregation level wasn’t granular enough for us to explore each genus of carnivorous plant we hoped to map. We’d need to start from scratch with the individual observations.<\/p>\n

Each observation in iNaturalist contains attributes such as species, location, time of day, and often a photo. This information contributes to the dataset being a reliable and invaluable source for scientists. It also allowed us to filter the observations<\/a> to the five carnivorous plant genera we wanted to map in our story.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2808422,"id":2808422,"title":"Blog_Filter_Genus","filename":"Blog_Filter_Genus.gif","filesize":432187,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-storymaps\/mapping\/mapping-inaturalist-observations-with-map-viewer\/blog_filter_genus","alt":"","author":"129801","description":"","caption":"Filtering the data can be an easy way to improve performance as well as decrease visual clutter on the map.","name":"blog_filter_genus","status":"inherit","uploaded_to":2808372,"date":"2025-05-26 16:06:28","modified":"2025-05-26 17:51:54","menu_order":0,"mime_type":"image\/gif","type":"image","subtype":"gif","icon":"https:\/\/www.esri.com\/arcgis-blog\/wp-includes\/images\/media\/default.png","width":749,"height":455,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus-213x200.gif","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","medium-width":430,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","medium_large-width":749,"medium_large-height":455,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","large-width":749,"large-height":455,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","1536x1536-width":749,"1536x1536-height":455,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","2048x2048-width":749,"2048x2048-height":455,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","card_image-width":749,"card_image-height":455,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/05\/Blog_Filter_Genus.gif","wide_image-width":749,"wide_image-height":455}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"

Aggregation<\/h2>\n

In mapping the observations of each plant throughout the story, we used aggregated hex bins to help with performance and visualizing the count of observations that would otherwise be difficult to discern from a mass of point symbols.<\/p>\n

The process for creating our aggregation of carnivorous plant observations involved:<\/p>\n