Sensitivity analysis and retrieval of optimum SLEUTH model parameters

The Cellular Automata (CA) based SLEUTH model has emerged as a widely applied to many cities for land use cover (LULC) change and urban growth modelling due its simplicity, robustness, ease of implementation. present study employed rigorous sensitivity testing self-modifying constants, Monte Carlo runs critical slope determine their influence on calibration performance. Calibration performance been examined in terms statistical measures i.e., area, clusters, edges, mean cluster size, radius, best fitness measure (i.e., Optimal Metrics (OSM)), overall accuracy percentage hit-miss-false alarm method have used. analysis reveals the optimum values parameters {1.3, 0.10, 0.90, 1.25} boom, bust, low high respectively; sixty (60) 15 simulate area.