LocationTech RasterFrames™ brings the power of Spark DataFrames to geospatial raster data, empowered by the map algebra and tile layer operations of GeoTrellis. The underlying purpose of RasterFrames is to allow data scientists and software developers to process and analyze geospatial-temporal raster data with the same flexibility and ease as any other Spark Catalyst data type. At its core is a user-defined type (UDT) called TileUDT, which encodes a GeoTrellis Tile in a form the Spark Catalyst engine can process. Furthermore, we extend the definition of a DataFrame to encompass some additional invariants, allowing for geospatial operations within and between RasterFrames to occur, while still maintaining necessary geo-referencing constructs.
Additional information can be found at the RasterFrames website: http://rasterframes.io/
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