GeoTrellis

Core features

• Working with Geopatial Data on Apache Spark

  • Generic way to represent key value RDDs as layers, where the key represents a coordinate in space based on some uniform grid layout, optionally with a temporal component.
  • Represent spatial or spatiotemporal raster data as an RDD of raster tiles.
  • Generic architecture for saving/loading layers RDD data and metadata to/from various backends, using Spark's IO API with Space Filling Curve indexing to optimize storage retrieval (support for Hilbert curve and Z order curve SFCs). Filesystem, S3, HDFS, Cassandra and Accumulo are supported.
  • Query architecture that allows for simple querying of layer data by spatial or spatiotemporal bounds.
  • Perform map algebra operations on layers of raster data, including all supported Map Algebra operations mentioned in the geotrellis-raster feature list.
  • Perform seamless reprojection on raster layers, using neighboring tile information in the reprojection to avoid unwanted NoData cells.
  • Pyramid up layers through zoom levels using various resampling methods.
  • Types to reason about tiled raster layouts in various CRS's and schemes.
  • Perform operations on raster RDD layers: crop, filter, join, mask, merge, partition, pyramid, render, resample, split, stitch, and tile.

• Working with Raster Data

  • GDAL bindings: read every supported raster format directly in GeoTrellis without a separate translation or ingest step.
  • RasterSource API provides a method of reading raster data from a variety of formats and sources, similar to a GDAL-like VRT feature.
  • Provides types to represent single- and multi-band rasters, supporting Bit, Byte, UByte, Short, UShort, Int, Float, and Double data, with either a constant NoData value (which improves performance) or a user defined NoData value.
  • Treat a tile as a collection of values, by calling "map" and "foreach", along with floating point valued versions of those methods.
  • Combine raster data in generic ways.
  • Render rasters via color ramps and color maps to PNG and JPG images.
  • Read GeoTiffs with DEFLATE, LZW, and PackBits compression, including horizontal and floating point prediction for LZW and DEFLATE.

• Working with Vector Data

  • Work directly with JTS types: Point, LineString, Polygon, MultiPoint, MultiLineString, MultiPolygon, GeometryCollection.
  • Provides a Feature type that is the composition of a geometry and a generic data type.
  • Read and write geometries and features to and from GeoJSON.
  • Read and write geometries to and from WKT and WKB.
  • Point cloud support with Voronoi Diagram and Delaunay Triangulation methods.