Raster Data I/O

The standard mechanism by which any data is brought in and out of a Spark Dataframe is the Spark SQL DataSource. RasterFrames provides specialized DataSources for geospatial raster data and maintains compatibility with existing general purpose DataSources, such as Parquet.

• Catalog Readers
  • aws-pds-l8-catalog: built-in catalog over Landsat on AWS
  • aws-pds-modis-catalog: built-in catalog over MODIS on AWS
  • geotrellis-catalog: for enumerating GeoTrellis layers
• Raster Readers
  • raster: the standard reader for most raster data, including single raster files or catalogs
  • geotiff: a simplified reader for reading a single GeoTIFF file
  • geotrellis: for reading a GeoTrellis layer
• Raster Writers
  • geotiff: beta writer to GeoTiff file format
  • geotrellis: creating a GeoTrellis layer
  • parquet: general purpose writer for Parquet

Furthermore, when in a Jupyter Notebook environment, you can view Tile and DataFrame samples.

There is also support for vector data for masking and data labeling.