This study aims to use the satellite data and Geographic Information System (GIS) to produce the soil map and use the spatial analysis technique to assess the soil capability. The soils adjacent to El-Manzala Lake east of the Nile Delta, Egypt were chosen for this application. To achieve this objective the land surveying, and satellite
data (Landsat ETM and SRTM images) were used in a Geographic Information System to delineate the landforms of the studied area. The correlation between landforms and soil taxonomic units were worked out. The results indicated that the area was dominated by flood plain (33.48 % of the total area), the lacustrine plain (21.52 % of the total area) and the marine plain (3.13 % of the total area). The Water bodies and urban areas exhibit 41.86 % of the total area. The soil properties such as CaCO3 content, texture class, soil depth, salinity, alkalinity, CEC and drainage condition were linked with the different landforms of the studied area. The thematic layers of these data were created in Arc-GIS 9.2 software using the spatial analysis function, and then these layers were matched together to assess the soil capability. The data obtained from the thematic layers indicate that the main limiting factors in the studied area were soil depth, drainage conditions, soil salinity, soil texture, alkalinity and calcium carbonate content. The limiting factors; CaCO3 %, soil depth, drainage condition, salinity and alkalinity were associated with the lacusrtine plain, while the soil texture and CEC were the main limiting factors in the marine plain. The soil depth, drainage condition and soil salinity were the dominating limiting factors of the flood plain.
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"Moore et al., 1993; Odeh et al., 1994; Florinsky et al., 2002; Park and Burt, 2002; Ziadat et al., 2003; Bishop et al., 2006; Liu et al., 2006; Castrignano et al., 2009), alsovariousbenefits related to the satellite data for mapping soil properties have been reported by many researchers (e.g. Frazier and Cheng, 1989; Bhatti et al., 1991; Liberti et al., 2009).Moreover information on spatial variance of topsoil properties becomes a must for land management (Ali and Kotb, 2010). Ordinary method for mappingthe topsoil properties is to collect samples using a grid sampling system, then; a prediction map can be made by interpolating the measured property values of the samples (Karydas et al., 2009). "
"The SPOT and IRS -PAN data offered stereo capability, which has improved the soil mapping efforts (Manchanda et al., 2002). The soil information so generated is interpreted for various purposes like land capability classification, land irrigability assessment, crop suitability studies, management of watersheds, prioritization of watersheds etc (Ali and Kotb, 2010 "