Spatial distribution analysis of soil variables for agronomic development in El-Omayed Area, North-Coastal of Egypt

Geostatistical modeling has recently been developed for spatial prediction of environmental variables. The current research aims to utilize geographic information capabilities, remote sensing imagery and soil data, for decision-making in natural resources management of El-Omayed area, N–W coast of E...

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Veröffentlicht in:Environmental earth sciences 2015-07, Vol.74 (1), p.889-901
Hauptverfasser: Darwish, Kh. M, Rashad, Mohamed, Mohamed, Sami Z, Gad, A
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Sprache:eng
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Zusammenfassung:Geostatistical modeling has recently been developed for spatial prediction of environmental variables. The current research aims to utilize geographic information capabilities, remote sensing imagery and soil data, for decision-making in natural resources management of El-Omayed area, N–W coast of Egypt. El-Omayed geographically limited by latitudes 30°45′N south and the Mediterranean Sea at the north. The selected region represents an extended territory having an area of 102,35 ha, and considers a promising location for future development, keeping the ecological protectorate site as a reference. It was possible to investigate the distribution of selected soil variables and their relation with the actual properties to carry out a detailed suitability evaluation for specific agricultural uses. Spatial patterns of some chemical and physical soil properties were analysed. Data were investigated both statistically and geostatistically based on the semivariogram analysis. Among the considered soil parameters, the spatial distribution model varied and showed moderate to strong spatial dependence. EC, gypsum and sand soil texture were strongly spatially dependent. Using a suitability model built in ALESarid software, the obtained results indicate that the area currently lacks high suitability classes. Following an improving soil properties program may enhance the soil capability status. An area of 70,109 ha (68.5 %) would become marginally suitable, then suitability for different common crops land use (wheat, sunflower, maize, olive, fig, onion, tomato, potato and watermelon) can elaborated. The usage of geospatial data, distribution analysis and GIS proved to be suitable tools to fulfill the needed large computational requirements.
ISSN:1866-6280
1866-6299
DOI:10.1007/s12665-015-4095-2