STUDY THE SPATIAL DISTRIBUTION OF SOIL PROPERTIES AND THEIR RELATIONSHIP TO THE SPECTRAL INDICES COMPUTED FROM THE SATELLITE IMAGE DATA

Remote sensing techniques have been used for the purpose of studying some soil characteristics and their relationship to the spectral indices computed from the satellite image data. The satellite image with an OLI sensor for the year 2020 with eleven spectral bands was used to calculate the spectral indices (NDVI, SI, GSI and CI). In preparing Supervised and Unsupervised classification maps, the aforementioned spectral indices values were extracted using the ArcMap10.4.1 program and then SPSS 22 was used to make correlations between the spectral indices and soil characteristics to find the best statistical relationships. 20 surface samples representing the study area were identified using the GPS device. Surface soil samples were taken for the purpose of conducting the required laboratory analyzes for the purpose of studying some physical and chemical characteristics. The results of the study showed the importance of using the NDVI index in the diagnosis and the spatial distribution of the vegetation cover and then its value appeared very low and this is an indicator of the weakness of agricultural investment in the study area and the results also show that the use of the SI index is of importance in determining and separating the spatial distribution of the soil salinity characteristic of the study area due to the presence of the influence relationship for this characteristic on the spectral reflectivity values directly or indirectly through its effect on the growth and density of vegetation, which increases the reflectivity of the soil surface, while the use of the GSI index is the best indices to predict the sizes of surface soil particles through spectral data, while the results indicated that the indices CI is an important index to describe the spatial heterogeneity in clay content of the study area and dry areas. The results of the spectral indices showed the presence of spatial variation in their values for the study area with significant relationships for the Normalized Difference Vegetation Index (NDVI), Salinity Index, (SI), Topsoil Grain Size Index (GSI) and the Clay index (CI), sand, silt, clay, gypsum, calcium carbonate, salinity and soil organic matter content.