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_RasterFrames™_ brings the power of Spark DataFrames to geospatial raster data, empowered by the map algebra and tile layer operations of [GeoTrellis](https://geotrellis.io/).
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_RasterFrames™_ brings the power of Spark DataFrames to geospatial raster data, empowered by the map algebra and tile layer
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operations of [GeoTrellis](https://geotrellis.io/).
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The source code can be found on GitHub at [s22s/raster-frames](https://github.com/s22s/raster-frames).
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The source code can be found on GitHub at [locationtech/rasterframes](https://github.com/locationtech/rasterframes).
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The underlying purpose of RasterFrames™ is to allow data scientists and software developers to process
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and analyze geospatial-temporal raster data with the same flexibility and ease as any other Spark Catalyst data type. At its
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RasterFrames™ is a new project under active development. Feedback and contributions are welcomed as we look to improve it.
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Please [submit an issue](https://github.com/s22s/raster-frames/issues) if there's a particular feature you think should be included.
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Please [submit an issue](https://github.com/locationtech/rasterframes/issues) if there's a particular feature you think should be included.
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*[Gitter Channel](https://gitter.im/s22s/raster-frames) [](https://gitter.im/s22s/raster-frames?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
description :="RasterFrames brings the power of Spark DataFrames to geospatial raster data, empowered by the map algebra and tile layer operations of GeoTrellis",
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