Predict Some Soil Characteristics And Prepare Their Digital Maps From Remote Sensing Data

Remote sensing techniques and geographic information systems have been used for the purpose of predicting some of the physical and chemical properties of the soil and preparing its digital maps from the remote sensing data of the satellite image sensor The Operational Land Imager(OLI) of the Landsat 8 satellite for the year 2019. Non-linear equations were prepared to predict maps of physical soil characteristics represented by soil content of clay, silt and sand and maps of chemical soil characteristics represented by soil salinity, sodium adsorption ratio, gypsum and organic matter by performing multiple regression analysis with the following spectral indices (NDVI, SI, GSI) , And with highly significant identification factors which amounted to (0.85, 0.81, 0.85, 0.92, 0.81, 0.89 and 0.82) for each of these characteristics, respectively. And through the high accuracy of the correlations between the predicted and laboratory-measured values of the characteristics, the spectral evidence used in the study proved its efficiency to predict these characteristics. In general, the best predictive mathematical equations were found for soil characteristics and with high significant correlation relationships (0.94, 0.89, 0.94, 0.97, 0.85, 0.93 and 0.90) for each of the studied soil characteristics.