# 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

- #### Temporal Resampling
    - **Time-based resampling** – upsample or downsample data along the time dimension

All methods work seamlessly with chunked (lazily loaded) [xarray.Datasets](https://docs.xarray.dev/en/stable/generated/xarray.Dataset.html) and are powered by [Dask](https://www.dask.org/) 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](https://xcube-dev.github.io/xcube-resampling/).
