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This is a blog version of a webinar that took place on April 16, 2024. Here’s a video of that webinar: Geospatial datasets representing information about real-world features such as points, lines, and polygons are increasingly large, complex, and multidimensional. They are naturally represented as vector data cubes: n-dimensional arrays where at least one dimension is a set of vector geometries. The Xarray ecosystem now supports vector data cubes thanks to Xvec, a package designed for working with vector geometries within the Xarray data model 🎉. For those familiar with GeoPandas, Xvec is to Xarray as GeoPandas is to Pandas. This blog post is geared toward analysts working with geospatial datasets. We introduce vector data cubes, discuss how they differ from raster data cubes, and de…