الفهرس 
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Abstract
Soil salinization is a global problem that affects a large part of the world, especially arid and semi-arid regions. Hence, diagnosing soil salinity is the first step towards appropriate management. The current work aims to assess and map soil salinity in the eastern Nile Delta using principal component analysis (PCA) as well as study the relationship between normalized difference vegetation index (NDVI) and the soil properties in study area to develop appropriate solutions for rational management to mitigate the impacts of soil salinization and increase yield production. A number of 34 soil profiles were dug that cover the variation in the soils located at the northeast of the Nile delta. The spatial variation of soil parameters was mapped using Ordinary Kriging interpolation using Arc GIS 10.5. Also, to monitor the variation of vegetation cover during the crop growth and their correlation with soil salinity, Operational Land Imager (OLI) Path/Row 176/39 with a spatial resolution of 30 meters was used during four dates in summer 2019 (June, July, August and september). ENVI, 5.1 Software (the Environment for Visualizing Images) was used for image processing and analyses of the OLI satellite data. NDVI was calculated based on the reflectance values in red (visible) and near infrared ranges, where high values of NDVI indicate good soil quality and vice versa. Four dates of NDVI were determined to track the change of vegetative density, which included the initial growth stage, then vegetative growth, flowering stage, and maturity and harvest stage SPSS was used to analyze the statistical relationship between soil salinity and NDVI. The results of PCA illustrated that, among the studied soil properties, soil electrical conductivity (ECe), sodium adsorption ratio (SAR), exchangeable sodium percent (ESP), and bulk density (BD), are the critical keys affecting the management practices in Nile Delta. Two Spatial management zones (SMZ) were identified; SMZ 1 occupied 45.04% of the study area and SMZ 2 occupied 54.96% of the study area. The average of soil pH, ECe, SAR, CEC, ESP and BD were 8.31, 20.32 dSm-1, 47.19, 32.9 cmolckg-1, 32.85% and 1.47 Mgm-3 for first cluster (SMZ1) respectively. In addition, the second cluster (SMZ2) has average of soil pH, ECe, SAR, CEC, ESP ad BD were 7.75, 12.30 dSm-1, 26.6, 25.23 cmolckg-1, 26.6% and 1.27 Mgm-3. The results showed that, p-value<0.05, which confirms that, there is a significant statistical difference between the two zones. Finally, the obtained results could be used as a fundamental base for improving the agricultural management practices in such salt-affected soils. The NDVI values in study area were varied from -0.06 to 0.40. Observed from results that there was highly negatively significant relationship between NDVI with salinity as well as sodicty, where the person correlation coefficient (r) values were -0.72, -0.49, -0.46, -0.35 of soil ECe, SAR, ESP and CaCO3, respectively, this indicates to increasing these variables leads to a decrease in NDVI. Also, the results cleared that there was no significant correlation between NDVI and CEC (r = -0.23) as well as soil pH (r = 0.08).Keywords: GIS, Remote sensing, Site-specific management zones, Normalized difference vegetation index, NDVI