Lowest-cost path analysis

Geostatistical techniques have gained widespread use in ecology and environmental science. Variograms are commonly used to describe and examine spatial autocorrelation, and kriging has become the method of choice for interpolating spatially-autocorrelated variables. To date, most applications of geostatistics have defined the separation between sample points using simple Euclidean distance. In heterogeneous environments, however, certain landscape features may act as absolute or semi-permeable barriers. This effective separation may be more accurately described by a measure of distance that accounts for the presence of barriers. Here we present an approach to geostatistics based on a lowest-cost path (LCP) function, in which the cost of a path is a function of both the distance and the type of terrain crossed. The modified technique was originally applied to 3 years of survey data on blue crab abundance in Chesapeake Bay.

The zipped archive below contains and ArcView (v. 8.3) script that was used to calculate the lowest-cost path between any two samples points on the map and associated Matlab m files to then take the intersample distance matrix created within ArcView to conduct the geostatistical analyses. There is a text file that contains the instructions for implementation.

To download the arhive simply right click on the link below and select Save As


Full details of the implementation of the algorithm are provided in a paper we published in Environmetrics in 2006 - available here. If you have any questions about implementation, do not hesitate to contact either Tom Miller or Olaf Jensen.

Jensen, O. P., M. J. Christman and T. J. Miller 2005. Landscape-based geostatistics: a case study of the distribution of blue crab in Chesapeake Bay. Environmetrics 00:000-000

Other blue crab papers

Last revised: 10/31/2007