RasterFrames 0.8.4 Released

Announce
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RasterFrames provides a DataFrame-centric view over arbitrary Earth-observation (EO) data, enabling spatiotemporal queries, map algebra raster operations, and compatibility with the ecosystem of Apache Spark ML algorithms. It provides APIs in Python, SQL, and Scala, and can scale from a laptop computer to a large distributed cluster, enabling global analysis with satellite imagery in a wholly new, flexible, and convenient way.

Changes 0.8.4

  • Upgraded to Spark 2.4.4
  • Add rf_mask_by_values and rf_local_is_in raster functions; added optional inverse argument to rf_mask functions. (#403, #384)
  • Added forced truncation of WKT types in Markdown/HTML rendering. (#408)
  • Add rf_local_is_in raster function. (#400)
  • Added partitioning to catalogs before processing in RasterSourceDataSource (#397)
  • Fixed bug where rf_tile_dimensions would cause unnecessary reading of tiles. (#394)
  • Breaking (potentially): removed GeoTiffCollectionRelation due to usage limitation and overlap with RasterSourceDataSource functionality.

Full release notes are available here: https://rasterframes.io/release-notes.html

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This is sweet! This is exactly what I might need for my satellite imagery project.

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