LAUSR

The purpose of this study is to identify potential areas of groundwater using remote sensing and GIS. Therefore, some of the effective layers were extracted such as geology, fractures and faults, geomorphology, slope, land use and regional drainage density using ETM sensing imagery processes such as producing various feature class codes, edge detection filters, regulated classification and imposing vegetation indices conducted by topographic maps of 1:50,000, geology and DEM. All layers were classified depending on their effectiveness based on the expert opinions, using analytic hierarchy process. They were also weighted in different classes. After modeling in GIS, groundwater’s potential of Semnan plains was determined in Iran. The results showed that the existence of fractures and fault in sandstone formations of Shemshak and gunpowder as well as thick limestone of the layer-formation of Lar have led to name these areas as highly well potential areas of groundwater. Then after, alluvial valleys, Stream sediments, foothills alluvial fans and alluvial plains have formed the well potential areas. Using the discharge of the 54 fountains, aqueduct and wells; the accuracy of the map was estimated through an error matrix method with an overall accuracy of 79.63 and Kappa coefficient of 0.702, which implies the good accuracy of this model.