Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. (2024). Assessment of Land Productivity Index Based on Parametric Approach Using GIS and Remote Sensing in Nubian Nasr Area, Aswan, Egypt. Aswan University Journal of Environmental Studies, 5(4), 510-527. doi: 10.21608/aujes.2024.322742.1287
Mohamed A.A Shaalan; Ahmed Ghallab; Ahmed Abd El-aziz Mahmoud Awad; Alaa Hashem Abd Elazem. "Assessment of Land Productivity Index Based on Parametric Approach Using GIS and Remote Sensing in Nubian Nasr Area, Aswan, Egypt". Aswan University Journal of Environmental Studies, 5, 4, 2024, 510-527. doi: 10.21608/aujes.2024.322742.1287
Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. (2024). 'Assessment of Land Productivity Index Based on Parametric Approach Using GIS and Remote Sensing in Nubian Nasr Area, Aswan, Egypt', Aswan University Journal of Environmental Studies, 5(4), pp. 510-527. doi: 10.21608/aujes.2024.322742.1287
Shaalan, M., Ghallab, A., Awad, A., Abd Elazem, A. Assessment of Land Productivity Index Based on Parametric Approach Using GIS and Remote Sensing in Nubian Nasr Area, Aswan, Egypt. Aswan University Journal of Environmental Studies, 2024; 5(4): 510-527. doi: 10.21608/aujes.2024.322742.1287
Assessment of Land Productivity Index Based on Parametric Approach Using GIS and Remote Sensing in Nubian Nasr Area, Aswan, Egypt
1Department of Soils and Natural Resources, Faculty of Agriculture and Natural Resources, Aswan University
2Department of soils and Natural Resources, Faculty of Agriculture and Natural Resources, Aswan University
Abstract
The main objective of this research was to determine the land productivity index based on a parametric approach using geographic information systems (GIS( and Remote sensing (RS). This study was conducted in the Nubian Nasr Area, located between 24° 27' 30"N and 24° 35' 0"N latitude, and 33° 0' 0"E and 33° 6' 0"E longitude, in Aswan Governorate, Egypt. The study area covers about 107.51Km^2 (10750.64 hectare). To achieve this objective, 27 soil profiles were chosen to cover the study area, and 81 soil samples were collected. Soil samples were analyzed for their parameters using the standard methods of soil analysis. Accordingly, land productivity was calculated for all studied soil profiles, and a result map was generated for the land productivity index utilizing GIS. According to the results, it was found that most of the land productivity for field crops, forage crops, and fruit trees was concentrated in the Average (III) class with rates of 51.85% (5574.21 hectares), 48.15% (5176.43 hectares), and 37.04% (3982.04 hectares), respectively. The second class, good (II) for agricultural use, came in second place with the following order: 25.93% (2787.64 hectares), 22.22% (2388.79 hectares), and 33.34% (3584.26 hectares) for field crops, forage, and fruit trees, respectively. The poor class (IV) represented 18.52% (1991.02 hectares) of field crops, 29.63% (3185.41 hectares) for forage crops, and 25.93% (2786.56 hectares) for fruit trees. The excellent class (I) represented about 3.71% (397.77 hectares) for both field crops and fruit trees, while it was nil for forage crops.
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