"},{"ID":4951,"user_firstname":"Ken","user_lastname":"Field","nickname":"Ken Field","user_nicename":"kenfield","display_name":"Kenneth Field","user_email":"KField@esri.com","user_url":"http:\/\/www.cartoblography.com","user_registered":"2018-03-02 00:16:36","user_description":"Maps are Ken\u2019s passion, and profession. After 20 years teaching cartography and GIS in academia in the UK he moved to California where, since 2011, he has made maps, and talked and written about cartography at Esri. He shares maps, videos, code, writings and how-tos at his Mappy Hour site (links.esri.com\/mappyhour), after 8 years as Chair is now Vice-Chair of the ICA Map Design Commission, and did a 9 year stint as Editor of The Cartographic Journal. He\u2019s won a few awards for maps, pedagogy, kitchen tile designs and his books 'Cartography.' and \u2018Thematic Mapping\u2019. He leads the Esri MOOC on Cartography which has had nearly 250,000 participants to date. He is a presenter of the Webby award winning Mappy Hour, and is co-founder of the popular mappery.org site. He was recently honoured by the Data Visualization Society with an \u2018Impressive Individual\u2019 Information is Beautiful award, and was voted as one of 100 professionals who have shaped the UK geo-industry. He snowboards (reasonably), plays drums (badly), is a lifelong supporter of his home-town Premier League football team Nottingham Forest, and has a tattoo of his favourite map on his arm.","user_avatar":"
"}],"short_description":"In ArcGIS Pro 3.5, we have just launched the first of a new toolset of cartogram generating tools, \u201cGenerate Contiguous Cartogram\u201d.","flexible_content":[{"acf_fc_layout":"content","content":"Not all maps look the same. Even maps of exactly the same place can look profoundly different. This is perhaps no more pronounced than when you see a cartogram which, let\u2019s be honest, pretty much destroys geography in order to try and emphasize some aspect of the thematic data it is trying to communicate. They\u2019re also divisive, in the sense that people tend to either love them or hate them. We\u2019ve even seen people argue over the relative merits. In the UK they\u2019d be referred to as \u201cMarmite\u201d \u2013 a yeast extract spread with a strong, salty, savoury flavour often enjoyed on toast for breakfast. But people either love it or hate it. Well, you\u2019ll be delighted to know there\u2019s folks at Esri who love cartograms (admittedly there\u2019s a few who don\u2019t\u2026 no names!). Over the years there have been various scripts and tools built as add-ins to support their construction in ArcMap and ArcGIS Pro. But now they\u2019re going primetime, and in ArcGIS Pro 3.5 (available mid-May) we are launching the first in a new toolset of cartogram generating tools.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nUsed for thematic mapping, cartograms are a particular class of map type where some aspect of the geometry of the map is modified to accommodate the problem caused by perceptually different geographies, such as the different sized areas on most choropleth maps. On choropleths, we have a tendency to see larger areas as more important, regardless of the variable being mapped, and this can cause confusion. Cartograms tackle this by modifying the geography itself, effectively normalizing the geography rather than the data variable to create a map where each area takes on a new shape and\/or size based on the variable being mapped. Cartograms therefore depict geographical space diagrammatically as they lose their relationship with true coordinate system geometry.<\/p>\n"},{"acf_fc_layout":"content","content":"
There are both benefits and drawbacks to these density-equalising cartograms. Whereas choropleth maps necessitate the conversion of data from totals into rates (e.g. percentages) to overcome the problems caused by different sized areas, cartograms are designed with totals in mind as the sizing of the output polygons negates any original differences in density. In fact, they don\u2019t perform as well with rates because rates have already done the job of normalization.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nCartograms broadly fall into one of four categories: contiguous, non-contiguous, graphical and gridded. Each of which represent the mapped variable differently as Ken explains in the GIS&T Body of Knowledge<\/a>. Dorling cartograms for example, which Ken has previously shared a Python toolbox<\/a> for, are a form of graphical cartogram. These are symbol-based and more abstract.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nThe first tool we have introduced with this new toolset is one that generates contiguous cartograms<\/strong>. These are maps where the sizes of polygons have been altered (contorted, warped, deformed, squashed, and stretched) to be directly proportional to a chosen numeric variable. Common examples include maps of population, election results, and gross national statistics.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nAdditionally, contiguous cartograms maintain the connectivity between adjacent geographical areas, i.e. neighbours remain neighbours. Preserving this spatial relationship while controlling the distortion to acceptable recognition was hailed as somewhat of a holy grail of cartograms until Michael Gastner and Mark Newman proposed the diffusion method of flow in 2004.
\n <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2760672,"id":2760672,"title":"WorldPopulation","filename":"WorldPopulation.png","filesize":335359,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/mapping\/marmite-maps-now-available-in-arcgis-pro\/worldpopulation","alt":"Side-by-side image showing the difference between a map of the world and a map of the world with countries resized based on their population.","author":"33851","description":"","caption":"","name":"worldpopulation","status":"inherit","uploaded_to":2760572,"date":"2025-04-16 20:58:51","modified":"2025-04-16 21:00:29","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":2900,"height":720,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation.png","medium-width":464,"medium-height":115,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation.png","medium_large-width":768,"medium_large-height":191,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation.png","large-width":1920,"large-height":477,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation-1536x381.png","1536x1536-width":1536,"1536x1536-height":381,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation-2048x508.png","2048x2048-width":2048,"2048x2048-height":508,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation-826x205.png","card_image-width":826,"card_image-height":205,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation-1920x477.png","wide_image-width":1920,"wide_image-height":477}},"image_position":"center","orientation":"horizontal","hyperlink":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/WorldPopulation.png"},{"acf_fc_layout":"content","content":"
\nCartograms can also give a good impression of data distribution; the ability to identify patterns and trends, or to visually emphasize dominance, influence and relationships. Because the areas have been normalized, the amount of colour you see on the page or screen is visually comparable to all other areas. Your cognitive system doesn\u2019t have to try and interpret large areas (possibly with low values) and small areas (possibly with large values but which are visually suppressed in the overall geographical map).<\/p>\n"},{"acf_fc_layout":"content","content":"
\nThe drawbacks? It\u2019s really just the loss of geographical fidelity, and the familiarity of a known set of shapes. We get quite wedded to the map as it exists geographically so to see it deformed can be a challenge (to the point of hatred apparently!). This issue becomes more acute the less familiar the geography is, or where data variables have such a large range that the distortion is too pronounced to be useful. It is for this reason that we\u2019d generally recommend the use of labels as ways to anchor the newly distorted shapes to a reality that is known. When you see a label for a place you know, it helps decipher the \u2018where\u2019 of what you\u2019re looking at.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nSo, how does the tool work?<\/strong>
\nThe first tool we\u2019re releasing in the new toolset is called \u201cGenerate Contiguous Cartogram\u201d and can be found in the Cartogram toolset under Cartography Tools. There are very few parameters to be concerned about.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nSimply choose the input feature class you wish to display as a cartogram and the numeric field you wish to size the output polygons by.
\n <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2760722,"id":2760722,"title":"GenerateCartogramTool","filename":"GenerateCartogramTool.png","filesize":11447,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/mapping\/marmite-maps-now-available-in-arcgis-pro\/generatecartogramtool","alt":"Generate continguous cartogram tool dialog","author":"33851","description":"","caption":"","name":"generatecartogramtool","status":"inherit","uploaded_to":2760572,"date":"2025-04-16 21:16:06","modified":"2025-04-16 21:16:47","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":421,"height":338,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","medium-width":325,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","medium_large-width":421,"medium_large-height":338,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","large-width":421,"large-height":338,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","1536x1536-width":421,"1536x1536-height":338,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","2048x2048-width":421,"2048x2048-height":338,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","card_image-width":421,"card_image-height":338,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/GenerateCartogramTool.png","wide_image-width":421,"wide_image-height":338}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"
\nChoose a name for the new feature class the tool will create, and your preferred method of the two options available: Flow-based, and Diffusion.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nThese terms are based on the original work of Gastner et al.<\/em> used as our foundation. Both methods adopt principles of fluid dynamics to resize and reshape polygons on a grid, allowing higher density regions to effectively flow into lower density ones, such that the areas become proportional to the chosen value while preserving topological relationships.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nThey differ in the choice of equations and the strategy used to perform the computation. The diffusion method reassesses more often the flux that controls the growing or shrinking of areas in order to complete the overall cartogram, while the flow-based method introduces smoothing of density variations (less and less as the process goes on) and linear interpolation to perform the transformations in small steps.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nThe detail of the two methods is somewhat immaterial\u2026 hit Run, sit back and give the tool a little time to process (hey, there\u2019s some complex Maths and Physics stuff going on in the background!), and simply see if you like the result. Try the two methods. Pick the version you like the look of the most. It\u2019s that simple.<\/p>\n"},{"acf_fc_layout":"content","content":"
\nWithout any changes to your coordinate system or projection, the tool will create a spatial grid, then iteratively warp it to resize each polygon based on your chosen attribute while maintaining the spatial relationship and shared edges between them. Polygon boundaries are then drawn back in their new positions and you get your new cartogram feature class containing the transformed polygons. Existing layer symbology and labelling are retained.
\n <\/p>\n"},{"acf_fc_layout":"image","image":{"ID":2761752,"id":2761752,"title":"CartogramGrid2","filename":"CartogramGrid2.png","filesize":238157,"url":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-pro\/mapping\/marmite-maps-now-available-in-arcgis-pro\/cartogramgrid2","alt":"An example of the warped grid used when generating a cartogram","author":"33851","description":"","caption":"","name":"cartogramgrid2","status":"inherit","uploaded_to":2760572,"date":"2025-04-16 23:47:11","modified":"2025-04-16 23:47:26","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":500,"height":286,"sizes":{"thumbnail":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2-213x200.png","thumbnail-width":213,"thumbnail-height":200,"medium":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","medium-width":456,"medium-height":261,"medium_large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","medium_large-width":500,"medium_large-height":286,"large":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","large-width":500,"large-height":286,"1536x1536":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","1536x1536-width":500,"1536x1536-height":286,"2048x2048":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","2048x2048-width":500,"2048x2048-height":286,"card_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","card_image-width":500,"card_image-height":286,"wide_image":"https:\/\/www.esri.com\/arcgis-blog\/app\/uploads\/2025\/04\/CartogramGrid2.png","wide_image-width":500,"wide_image-height":286}},"image_position":"center","orientation":"horizontal","hyperlink":""},{"acf_fc_layout":"content","content":"