Year: 2025
Type: article
Abstract: In the current work, a land capability classification by integrating remote sensing and GIS technologies was implemented within an area of 30282 ha in the western Nile Delta region. Soil samples collected from seventy soil profiles were analyzed for physicochemical properties. Using ArcGIS software, the soil raster layers were created using the IDW (inverse distance weighting) interpolation technique. Thereafter, the slope and soil layers were transformed to a unitless score (from 0 to 1) via the fuzzy linear membership function, overlain through the fuzzy Gamma operator, and finally, the single layer was categorized using the natural breaks classifier. Results revealed the studied region exhibited a wide variability of land capability ranging from excellent (C1) to very poor (C5). Lands classified as C1 covered 831,600 ha, representing about 27% of the total area. Moreover, the lands with good capability (C2) occupied 1,069,900 ha, accounting for about 36% of the total area. Areas classified as C1 and C2 were mainly found in the middle parts due to the presence of slight limitations. The fair lands (C3) covered 701,300 ha (23%) in the northeastern and southwestern parts, where moderate chemical and physical soil limitations were observed. The lands with poor (C4) and very poor capabilities occurred in 111,500 and 151,700 ha, representing about 4 and 5% of the total area, respectively. These lands were mainly observed in small and scattered areas across the region, where severe and very severe limitations occurred. The most crucial soil limitations were salinity, rooting depth, and lime content.
Institution: Benha University
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
SDGs: Life on land, Zero hunger
Open Access status: bronze
OpenAlex ID: W7117453286
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