What’s New with USA Federal Lands in the Living Atlas

The ArcGIS Living Atlas of the World contains vector and raster layers for lands managed or owned by six agencies of the federal government (US Fish and Wildlife Service, National Park Service, US Forest Service, Bureau of Land Management, Bureau of Reclamation, Department of Defense). Last week, these Esri owned layers were updated, including the addition of two new agencies, more accurate ownership attribution, faster drawing speeds, and access to the latest features in ArcGIS Pro.


The USA Federal Lands feature layer provides access to vector data for all six agencies. In ArcGIS Online, the feature layer can be filtered and new feature layer views of the data saved as layers:

The new USA Federal Lands feature layer is best for visualization at larger scales (> 1:2,000,000) and can be combined with an imagery layer or a tile layer in a web map to provide fast rendering across the entire range of scales.

In ArcGIS Online you can export the feature layer’s data, perform analysis, change symbology, and work with the layer’s attribute table to select features and edit data. In ArcGIS Pro you can do even more including using the layer as an analytic input to a geoprocessing tool, model, or Python script.


The USA Federal Lands imagery layers were also updated with the same data used to create the feature layers. Like the feature layer, raster functions and filters allow us to create views of subsets of the data. We created imagery layers for each of the six federal agencies in the data set:

Imagery layers are useful online to rapidly draw across the entire scale range and can be used in web maps to support the feature service at smaller scales. Imagery layers are particularly useful in ArcGIS Pro where you can use functions to extract, modify, and combine imagery layers on the fly to create landscape models that reveal patterns in the data.

These layers are part of the ArcGIS Living Atlas of the World, which provides an easy way to explore many other authoritative maps on hundreds of topics like this one.

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