Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. (2025). Using geostatistics and GIS approaches to characterize and map soil spatial variability in the Nubian Nasr Area of Aswan Governorate, Egypt. Aswan University Journal of Environmental Studies, 6(1), 63-80. doi: 10.21608/aujes.2025.352657.1318
Mohamed Shaalan; Ahmed Ghallab; Ahmed Abd El-aziz Mahmoud Awad; Alaa Hashem Abd Elazem. "Using geostatistics and GIS approaches to characterize and map soil spatial variability in the Nubian Nasr Area of Aswan Governorate, Egypt". Aswan University Journal of Environmental Studies, 6, 1, 2025, 63-80. doi: 10.21608/aujes.2025.352657.1318
Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. (2025). 'Using geostatistics and GIS approaches to characterize and map soil spatial variability in the Nubian Nasr Area of Aswan Governorate, Egypt', Aswan University Journal of Environmental Studies, 6(1), pp. 63-80. doi: 10.21608/aujes.2025.352657.1318
Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. Using geostatistics and GIS approaches to characterize and map soil spatial variability in the Nubian Nasr Area of Aswan Governorate, Egypt. Aswan University Journal of Environmental Studies, 2025; 6(1): 63-80. doi: 10.21608/aujes.2025.352657.1318
Using geostatistics and GIS approaches to characterize and map soil spatial variability in the Nubian Nasr Area of Aswan Governorate, Egypt
1Soil and Natural Resources Department, Faculty of Agriculture and Natural Resources, Aswan University, Aswan 81528, Egypt.
2Soil and Natural Resources Department, Faculty of Agriculture and Natural Resources, Aswan University, Aswan 81528, Egypt.
3Department of Soils and Natural Resources, Faculty of Agriculture and Natural Resources, Aswan University
Abstract
Precision agriculture heavily relies on detailed spatial information about soil characteristics to promote long-term soil and plant health. The present research sought to evaluate, predict, map, and analyze the spatial variability of physicochemical properties in the Nubian Nasr Area of Aswan Governorate. Soil properties were measured, including electrical conductivity, texture, organic matter, calcium carbonate, pH, cation exchange capacity, exchangeable sodium percentage, available nutrients, and sodium absorption ratio. The mean values of the studied soil properties ranged from 2.85 to 449.58, with high values observed for available potassium, sand, available nitrogen, and CEC, and low values for other properties. The geographical distribution of these attributes was mapped and characterized using classical and geostatistical approaches. Spatial variability was quantified using semi-variogram models, and maps of projected values were created using ordinary kriging. Results indicated significant spatial variability in soil properties, with strong correlations between certain parameters. The semi-variogram models that were determined to be best appropriate for the qualities under study were the exponential, Gaussian, K-Bessel, and J-Bessel models. The maps produced offer vital data for precision farming, allowing customized management plans to enhance soil health. Geostatistical techniques effectively characterized, predicted, and mapped spatial soil variability.
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