Abstract
—The challenge faces the world in the coming decades is to provide an adequate food supply for increasing populations. The food supply should be granted to 6 billion inhabitants on 2000 and excepted 8 billion people in 2025. Food supply shortages occurs in arid and semiarid zones where a land degradation and desertification are the main obstacles facing sustainable agriculture. Soil Salinisation is one of the most common land degradation processes in arid and semi-arid regions, where evaporation exceed over precipitation. Under such climatic conditions, soluble salts are accumulated in the soil, influencing soil properties and environment with ultimate decline in soil productivity. Therefore, mapping of saline areas is essential for understanding resource for sustainable soil uses and management. This paper presents a model to map soil salinity using Remote Sensing (RS) and Geographic Information Systems (GIS). The model development consists of a number of phases, salinity detection using RS data, site observations, correlation and verification, and validation. Multi–temporal Landsat-7 ETM image (Enhanced Thematic Mapper) acquired in 2000 and 2002 were used to detect coastal saline areas. GIS was used to integrate the available data and information, design the model, and to create different maps. The correlation between the salinity maps developed from visual interpretation of remote sensing data, and site observations shows that the saline areas delineated using remote sensing data fits with those delineated using site observations data. The study confirmed that ground truth coupled with RS data and GIS techniques are powerful tools in detecting salinity at different levels in arid conditions. The model can be adopted elsewhere in similar areas that experience salinisation problems