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  4. LocationTech RasterFrames™

LocationTech RasterFrames™

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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/

Working Group: 
LocationTech
Licenses: 
Apache License, Version 2.0

The content of this open source project is received and distributed under the license(s) listed above. Some source code and binaries may be distributed under different terms. Specific license information is provided in file headers and in NOTICE files distributed with the project's binaries.

Active Member Companies: 
Member companies supporting this project over the last three months.
    Contribution Activity: 
    Commits on this project (last 12 months).

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    Incubating - LocationTech RasterFrames™

    Related Projects

    Related Projects:

    • LocationTech
      • LocationTech GeoTrellis
      • LocationTech GeoMesa™

    Project Hierarchy:

    • LocationTech
    • LocationTech RasterFrames™

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    • Apache Spark
    • Machine Learning
    • Raster
    • DataFrame

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