Although most often we are interested in characterizing the straightline, or Euclidean, distance among objects in the landscape, there are many other distance measures that are relevant to the field of geospatial analysis. One of the more useful distance measures is the cost-distance, which is related to the cost of traversing a distance, along a specific path, through a landscape containing varying costs. The cost can be thought of as any form of friction or resistance to movement across some distance, usually a grid cell in the case of raster GIS. For example, the cost of traversal might be an actual cost such as that associated with travelling a distance along a toll highway, or it could be the cost of fuel, or even the travel time. It is very broadly a factor associated with travelling a distance through a diverse landscape that should be minimized. Cost surfaces can be used to describe the costs associated with travelling through each grid cell in a raster dataset and can take into account any number of cost factors, such as local slope gradient, visibility, landscape barriers (e.g. streams and other waterbodies), soil type, etc. The objective of a least-cost pathway analysis is to find the pathway or set of pathways that minimize the cost of traversing from a source area or group of source areas to a destination or group of destinations through a landscape of varied associated costs described by the cost surface. This represents a very powerful form of GIS-based analysis with widespread application in many problem domains. Typcial examples include planning the routes of roads, power lines, or pipelines.
In Whitebox, cost-distance and least-cost analyses are carried out using three related tools including: 1) Cost Accumulation, 2) Cost Allocation, and 3) Cost Pathway.