Comparing raster map comparison algorithms for spatial modeling and analysis

The comparison of spatial patterns is recognized as an important task in landscape ecology especially when spatially explicit simulation modeling or remote sensing is applied. Yet, there is no agreed procedure for doing that, probably because different problems require different algorithms. We explored a variety of existing algorithms and modified some of them to compare grid-based maps with categorical attributes. A new algorithm based on the expanding window approach was developed and compared to other known algorithms. The goal was to offer simple and flexible procedures for comparing spatial patterns in grid based maps that do not take into consideration object shapes and sizes of the maps. The difference between maps was characterized by three values: quantity, location, and distance between corresponding categories in the maps, Combinations of these indices work as good criteria to quantify differences between maps. A web-based survey was set up, in which participants were asked to grade the similarity of ten pairs of maps. These results were then used to compare how well the various algorithms can perform relative to the visual comparisons obtained; they were also used to calibrate existing algorithms.