Utilities#

Mahalanobis Distance#

xrspatial.mahalanobis.mahalanobis(bands[, ...])

Compute per-pixel Mahalanobis distance from a multi-band reference.

Emerging Hotspots#

xrspatial.emerging_hotspots.emerging_hotspots(...)

Classify time-series hot spot and cold spot trends.

Polygonize#

xrspatial.polygonize.polygonize(raster[, ...])

Polygonize creates vector polygons for connected regions of pixels in a raster that group together by pixel value.

Rasterize#

xrspatial.rasterize.rasterize(geometries[, ...])

Rasterize vector geometries into a 2D DataArray.

Contours#

xrspatial.contour.contours(agg[, levels, ...])

Extract contour lines (isolines) from a raster surface.

Preview#

xrspatial.preview.preview(agg[, width, ...])

Downsample a raster to target pixel dimensions.

Normalization#

xrspatial.normalize.rescale(agg[, new_min, ...])

Min-max normalization of a raster to a target range.

xrspatial.normalize.standardize(agg[, ddof, ...])

Z-score normalization of a raster.

Overlap Fusion#

xrspatial.utils.fused_overlap(agg, *stages)

Run multiple overlap operations in a single map_overlap call.

xrspatial.utils.multi_overlap(agg, func, ...)

Run a multi-output kernel via a single overlap + map_blocks call.

Rechunking#

xrspatial.utils.rechunk_no_shuffle(agg[, ...])

Rechunk a dask-backed DataArray or Dataset without triggering a shuffle.

Diagnostics#

xrspatial.diagnostics.diagnose(agg[, tool])

Diagnose a DataArray for common xarray-spatial pitfalls.