GeoTrellis

GeoTrellis is a Scala library and framework that uses 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.

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

• Gitter
• GeoTrellis mailing list

Example

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

scala> import geotrellis.raster.op.focal._
import geotrellis.raster.op.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 asciiDraw method is mostly useful when you're working with small tiles
// which can be taken in at a glance
scala> iat.asciiDraw()
res0: String =
"    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

"

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

Index of ReadMe docs

Throughout this repo, you'll find readme documents specific to particular the modules in which they're found.

1. deploy-ec2 - deploying GeoTrellis on AWS EC2
2. geotrellis.graph - experimental code for converting to/from RasterRDDs and GraphX
3. geotrellis.proj4 - converting raster data between projections
4. geotrellis.raster - documentation about creating and using raster data
5. geotrellis.raster.imagery - cloud removal with multi-band imagery
6. geotrellis.raster.interpolation - Kriging interpolation from raster data
7. geotrellis.raster.io
8. geotrellis.raster.op - Map Algebra operations
9. geotrellis.raster.render - rendering results as PNGs
10. geotrellis.raster.resample - changing a tile's resolution
11. geotrellis.vector - creating and using vector data
12. geotrellis.vector.interpolation - Kriging interpoloation from vector point data
13. geotrellis.vector.io.json - parsing vector data as GeoJSON
14. spark-etl - ingesting raster data and storing as Raster RDDs using Spark
15. spark - performing raster operations on Raster RDDs using Spark

API Reference

Scaladocs for the latest version of the project can be found here:

http://geotrellis.github.com/scaladocs/latest/#geotrellis.package

Contributors

• Josh Marcus
• Erik Osheim
• Rob Emanuele
• Adam Hinz
• Michael Tedeschi
• Robert Cheetham
• Justin Walgran
• Eric J. Christeson
• Ameet Kini
• Mark Landry
• Walt Chen
• Eugene Cheipesh

Contributing

Feedback and contributions to the project, no matter what kind, are always very welcome. A CLA is required for contribution, see the CLA FAQ on the wiki for more information. Please refer to the Scala style guide for formatting patches to the codebase.