Packages

o

geotrellis.spark.costdistance

IterativeCostDistance

object IterativeCostDistance

This Spark-enabled implementation of the standard cost-distance algorithm mentioned in the "previous work" section of [1] is "heavily inspired" by the MrGeo implementation [2] but does not share any code with it.

1. Tomlin, Dana. "Propagating radial waves of travel cost in a grid." International Journal of Geographical Information Science 24.9 (2010): 1391-1413.

2. https://github.com/ngageoint/mrgeo/blob/0c6ed4a7e66bb0923ec5c570b102862aee9e885e/mrgeo-mapalgebra/mrgeo-mapalgebra-costdistance/src/main/scala/org/mrgeo/mapalgebra/CostDistanceMapOp.scala

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. IterativeCostDistance
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Type Members

  1. type Changes = ArrayBuffer[KeyCostPair]
  2. class ChangesAccumulator extends AccumulatorV2[KeyCostPair, Changes]

    An accumulator to hold lists of edge changes.

  3. type KeyCostPair = (SpatialKey, Cost)

Value Members

  1. def apply[K, V](friction: RDD[(K, V)] with Metadata[TileLayerMetadata[K]], geometries: Seq[Geometry], maxCost: Double = Double.PositiveInfinity)(implicit arg0: (K) ⇒ SpatialKey, arg1: (V) ⇒ Tile): RDD[(K, Tile)] with Metadata[TileLayerMetadata[K]]

    Perform the cost-distance computation.

    Perform the cost-distance computation.

    friction

    The friction layer; pixels are in units of "seconds per meter"

    geometries

    The starting locations from-which to compute the cost of traveling

    maxCost

    The maximum cost before pruning a path (in units of "seconds")