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create masks of geospatial regions for arbitrary grids

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create masks of geospatial regions for arbitrary grids

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When working with gridded data such as climate model output or reanalysis data it is often important to create regional averages, e.g., over countries, continents or regions defined in the literature. To do so we need to know for each grid point to which region it belongs to.

regionmask is a python package that:

  • can be used to create masks of (geo)spatial regions for arbitrary (longitude and latitude) grids. These masks indicate which region a gridpoint belongs to and can then be used to aggregate gridded data over the regions. The masks come in three variants:
    • 2D integer masks
    • 3D boolean masks
    • 3D approximate fractional masks
  • takes great care to create consistent masks for
    • region edges and interiors
    • overlapping regions
  • contains a number of defined regions, including:
    • countries
    • landmasks
    • regions used in the scientific literature
  • can plot figures of these regions
  • supports using arbitrary existing or user-defined region definitions:
    • regions defined as shapefiles can be accessed via geopandas
    • user-defined regions can be created via numpy or shapely


Learn more about regionmask in its official documentation at

Get in touch

Dont hesitate to ask usage questions, report bugs, suggest features or view the source code on GitHub under regionmask/regionmask.


regionmask is published under a MIT license.

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