Population density us map series#

Latitude (continuous dimension, latitude geographic role assigned) Longitude (continuous dimension, longitude geographic role assigned) Basic map building blocks: Columns shelf:

Density marks work best where the specific locations change continuously and smoothly across space, rather than values constrained to discrete locations like borough or neighborhood. Tableau can recognize location names and create a density map using the point locations assigned to Tableau geocoding locations, but density maps are most effective when the location data is very precise, such as location coordinates in a limited space. To create a density map, your data source should contain point geometry, latitude and longitude coordinates, or location names (if recognized as location names by Tableau). They are most effective when working with a data set containing many data points where there’s substantial overlap between the marks on the map. Tableau creates density maps by grouping overlaying marks and color-coding them based on the number of marks in the group.ĭensity maps help you identify locations with greater or fewer numbers of data points. One common map type for this is a density map, also called a heatmap. You'll connect with a community of like-minded readers who are passionate about contemporary art, read articles and newsletters ad-free, sustain our interview series, get discounts and early access to our limited-edition print releases, and much more.You can create maps in Tableau that reveal patterns or relative concentrations that might otherwise be hidden due to overlapping marks on a map. #cartography #data #maps #population #Spencer Schien #technologyĭo stories and artists like this matter to you? Become a Colossal Member today and support independent arts publishing for as little as $5 per month. Atlanta, for example, is more than 137 square miles with around 4,200 people per square mile, and the map illustrates this as a mass of red amidst surroundings of more rural areas in green.Ĭurrently based in Milwaukee where he works as the Senior Manager of Data & Analytics for City Forward Collective, Schien focuses on building the maps and other statistical visualizations using open-source tools that help to alleviate financial barriers to information. You can find more of his work on his website. The more densely populated an area is, the higher the bars rise. He then translates statistical information about specific regions into highly contrasted maps utilizing Rayshader. To compile the maps, Schien digs into the Kontur Population dataset, a publicly accessible project that layers global population numbers derived from sources like the Global Human Settlement Layer-a tool for assessing the presence of people on the planet-along with Microsoft’s Building Footprints and Facebook. In his work with nonprofits and NGOs, he uses R programming language to generate data visualizations that help organizations target where their services are most needed.

Population density us map series#

It’s one thing to know that Chicago is the third largest city in the United States or that the fastest growing metropolitan areas are in the West and the South, but how can we see it? Data technologist Spencer Schien answers that question with an ongoing series of population density maps of states, rivers, and coastlines. All images © Spencer Shien, shared with permission