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What is GeoTrellis?

GeoTrellis is a Scala library and framework that uses Apache Spark to work with raster data. It is released under the Apache 2 License.

GeoTrellis reads, writes, and operates on raster data as fast as possible. It implements many Map Algebra operations as well as vector to raster or raster to vector operations.

GeoTrellis also provides tools to render rasters into PNGs or to store metadata about raster files as JSON. It aims to provide raster processing at web speeds (sub-second or less) with RESTful endpoints as well as provide fast batch processing of large raster data sets.

Please visit the project site for more information as well as some interactive demos.

Why GeoTrellis?

Raster processing has traditionally been a slow task, which has prompted advances in vector data processing as an alternative. Raster data isn't going anywhere, however, with more and more satellite data made public every year. GeoTrellis is an answer to the growing need for raster processing at scale. We personally have handled terabyte-level data sets, but really we are only bound by the theoretical limits of Apache Spark. By scale then, we mean arbitrarily large.

Contact and Support

You can find more information and talk to developers (let us know what you're working on!) at:

Hello Raster!

Here's a small example showing a routine focal operation over a single Tile:

scala> import geotrellis.raster._
import geotrellis.raster._

scala> import geotrellis.raster.render.ascii._
import geotrellis.raster.render.ascii._

scala> import geotrellis.raster.mapalgebra.focal._
import geotrellis.raster.mapalgebra.focal._

scala> val nd = NODATA
nd: Int = -2147483648

scala> val input = Array[Int](
     nd, 7, 1, 1,  3, 5, 9, 8, 2,
      9, 1, 1, 2,  2, 2, 4, 3, 5,
      3, 8, 1, 3,  3, 3, 1, 2, 2,
      2, 4, 7, 1, nd, 1, 8, 4, 3)
input: Array[Int] = Array(-2147483648, 7, 1, 1, 3, 5, 9, 8, 2, 9, 1, 1, 2,
2, 2, 4, 3, 5, 3, 8, 1, 3, 3, 3, 1, 2, 2, 2, 4, 7, 1, -2147483648, 1, 8, 4, 3)

scala> val iat = IntArrayTile(input, 9, 4)  // 9 and 4 here specify columns and rows
iat: geotrellis.raster.IntArrayTile = IntArrayTile([I@278434d0,9,4)

// The renderAscii method is mostly useful when you're working with small tiles
// which can be taken in at a glance.
scala> iat.renderAscii(AsciiArtEncoder.Palette.STIPLED)
res0: String =
∘█  ▚▜██▖
█  ▖▖▖▜▚▜
▚█ ▚▚▚ ▖▖
▖▜█ ∘ █▜▚

scala> val focalNeighborhood = Square(1)  // a 3x3 square neighborhood
focalNeighborhood: geotrellis.raster.op.focal.Square =
 O  O  O
 O  O  O
 O  O  O

scala> val meanTile = iat.focalMean(focalNeighborhood)
meanTile: geotrellis.raster.Tile = DoubleArrayTile([D@7e31c125,9,4)

scala> meanTile.getDouble(0, 0)  // Should equal (1 + 7 + 9) / 3
res1: Double = 5.666666666666667

Ready? Setup a GeoTrellis development environment.

.. toctree::
   :maxdepth: 2
   :caption: Home
   :hidden:

   Changelog <CHANGELOG>
   Contributing <CONTRIBUTING>

.. toctree::
   :maxdepth: 3
   :caption: Tutorials
   :glob:
   :hidden:

   tutorials/setup
   tutorials/quickstart
   tutorials/kernel-density
   tutorials/reading-geoTiffs
   Extract-Transform-Load (ETL) <tutorials/etl-tutorial>

.. toctree::
   :maxdepth: 4
   :caption: User Guide
   :glob:
   :hidden:

   guide/core-concepts
   Using Rasters <guide/rasters>
   Using Vectors <guide/vectors>
   Spark and GeoTrellis <guide/spark>
   The ETL Tool <guide/etl>
   Extending GeoTrellis Types <guide/extending-geotrellis>
   GeoTrellis Module Hierarchy <guide/module-hierarchy>
   Tile Layer Backends <guide/tile-backends>
   Vector Data Backends <guide/vector-backends>
   Frequently Asked Questions <guide/faq>
   Example Archive <guide/examples>

.. toctree::
   :maxdepth: 2
   :caption: Architecture
   :glob:
   :hidden:

   Architecture Decision Records <architecture/adrs>
   Proj4 Implementation <architecture/proj4-implementation>
   architecture/high-performance-scala