Abstract
Unsuitable practices and improper land management lead to soil degradation and therefore deviates land from optimum productivity. Remote sensing indices and spatial variability of soil properties were implemented in Arc GIS model-Builder for quantitative assessment of land degradation in Siwa Oasis, western desert, Egypt. Semivariogram model through Kriging techniques was used to produce maps of soil properties in two dates 2002 and 2017. This was done in order to calculate soil degradation rates and its areas in the studied area. The results indicated that geostatistical approach and ArcGIS model-builder can directly reveal the spatial variability of soil properties and measure accurately the changes in soil properties. The results will help the farmers and decision makers for improving the soil-water management. The cross-validation results illustrated the smoothing effect of the spatial prediction. Physical and chemical properties of 90 soil profiles were analyzed and chemical parameters were analyzed of 30 groundwater sample, collected from irrigation-wells. Landsat images of five different periods were collected to monitor the changes of the surface features of soil salinity and water logging. Soil analyses show a wide variability. The very saline, non-sodic soils cover most of the suited soils. Agricultural areas, saline soils and water logged areas were increased. The increment of saline soil and water logged areas is associated with poor drainage and increment in crop irrigation. There is degradation in groundwater quality which indicated by its salinity. The studied soils are salt-affected and this prompts the need of a proper land reclamation program and prods the development of effective irrigation and drainage systems.
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More From: Remote Sensing Applications: Society and Environment
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