Spatial Simulation and Land-subsidence Susceptibility Mapping Using Maximum Entropy Model

The aim of this research is spatial Simulation and land subsidence susceptibility mapping using maximum entropy model in Jiroft and Anbarabad Townships. At first, land subsidence locations were recognized using extensive field surveys and subsequently the land subsidence distribution map was made in the geographic information system. Then, each of effective factors on land subsidence occurred in study area such as: percent slope, aspect direction, altitude classes, profile curvature, plan curvature, topographic wetness index (TWI), distance of drainage, litology units, pizometric data, land use, and normalized difference vegetation index (NDVI) digitized in GIS environment. Then, using frequency ratio (FR) method, the weight of the classess of each factor and was determined. Finally, land subsidence susceptibility map in the study area was prepared using the model maximum entropy. The results of validation of model using 30% of the unused points in the modeling process and according receiver operating characteristic (ROC) showed that the map of land subsidence susceptibility obtained from the maximum entropy had the high accuracy of ARC value of 0.859 (85.9%). Therefore, the zoning map can play a significant role in water resource management and identification of critical areas according to extracting groundwater table in the study area.