The Role of Landscape Metrics and Spatial Processes in Performance Evaluation of GEOMOD (Case Study: Neka River Basin)

Performance evaluation is crucial for land cover change modeling. The main objective of this study is performance evaluation of GEOMOD using landscape metrics and spatial processes in landscape transformation for modeling change patterns of forest cover in Neka River Basin, north of Iran. Therefore, the land cover maps for the years 1984, 2001, and 2010 were used as the observed land cover maps. Suitability map from forest to non-forest was produced using weighted linear combination algorithm. Fuzzy membership functions and analytical hierarchy process were used to standardization and weight of criteria, respectively. We calculated the indices including class area, patch density, edge density, mean fractal dimension index, interspersion and juxtaposition index, effective mesh size, and mean related circumscribing circle using Fragstats and spatial processes using decision tree algorithm in Land Change Modeler. The relative error obtained by comparison of observed map versus simulated map for patch density, related circumscribing circle, and for effective mesh size metrics was the highest. The model was able to predict shape complexity, fragmentation, compactness and spatial heterogeneity, and area of forest class with high consistency. Landscape transformation analysis determined attrition according to the decrease in patch density and area of forest. Besides, the model predicted the same spatial process. The results of this research showed that this method can produce comprehensive information with high performance from uncertainty of result accuracy.