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xcube-resampling

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xcube-resampling provides efficient algorithms for transforming datasets into different spatial grids and temporal scales. It is designed for geospatial workflows that need flexible resampling and reprojection. This library provides up and downsampling for both spatial and temporal domains.

✨ Features

  • Spatial Resampling

    • Affine resampling – simple resampling using affine transformations
    • Reprojection – convert datasets between different coordinate reference systems (CRS)
    • Rectification – transform irregular grids into regular, well-structured grids
    • Grid extension – extend a regular grid to a requested bounding box, padding uncovered pixels
    • Mosaicking – combine tiles on a common regular grid, with deterministic overlap handling
  • Temporal Resampling

    • Time-based resampling – upsample or downsample data along the time dimension

All methods work seamlessly with chunked (lazily loaded) xarray.Datasets and are powered by Dask for scalable, out-of-core computation.

⚡ Lightweight & Independent

The package is independent of the core xcube framework and has minimal dependencies: affine, dask, dask-image, numba, numpy, pyproj, xarray.

Find out more in the xcube-resampling Documentation.

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