Identification Salt Crusts by using ASTER and LISSIII Data’s, Case Study: Regions of Iran

Salts tend concentrate on the soil surface in dry and irrigated areas. As salinity increases, more salts will paper at the soil surface, favoring the use of conventional remote sensing tools. Rapid identification and large-scale mapping of salt-affected soils will help improve salinity management in watersheds and ecosystems. Remote sensing data for the reason of broad and integrated view, better capability for calibration and multi spectral and temporal data are useful tools for identifying salt. Potentiality of various sensors is important in detecting salt crusts. Therefore, in this study we evaluated the data of ASTER & LISSIII sensors in order to identification salt crusts in Playas of DAMGHAN, KASHAN and MAHARLOO regions, IRAN. The first, the imageries corrected and then we used principal component analysis (PCA), normalize difference vegetation index (NDVI) and band rationing in detecting of salt crusts. In the band rationing method, two indices were applied, normalized difference salt crust index (NDSCI) and ratio salt crust index (RSCI). Investigation of feature space graphs in salt and non-salts crusts indicated that NDSCI and RSCI had the best separability. Then, the maps of these salt crusts prepared. In these maps, salt crusts were perfectly clear. In applied approaches showed, band rationing and using of these two indexes (NDSCI and RSCI) were very efficient. In addition, in general the ASTER data were better than of LISSIII data in separation of salt and non-salts crusts.

کلیدواژه ها:

ASTER Data ، LISS III Data ، salt crusts ، remote sensing