Geomatics and smart tools in Digital Land Resources Mapping and Sustainability of Coastal Agriculture, Egypt

Abstract

The northwestern coast of Egypt is characterized by an international interest due to its history and magnificent environment. The area was known as being the bread basket during the Greek and Roman periods. Recently, drastic changes in land use resulting in destructing many of water harvesting tools, thus diminution of the agriculture importance. Restoration of the area and planning self-sufficient communities needs to develop a sustainable land resources database for these regions. Multi concept of remote sensing and the Geographic Information System (GIS) permit to store, merge, and manipulate the huge amounts of thematic maps and attribute data. Sentinel satellite image 2018 scenes, covering the study area at the Egyptian northwestern coast, were acquired. ENVI software was used for image processing. A number of 53 topographic maps at scale 1:50000 were used to input GIS thematic layers relevant to land resources, using Arc_GIS 10.2 system. Field investigation was carried out to represent different soil units and collect ground control points. Chemical and physical soil properties were determined to assist soil classification. Soil map was produced including dominant geographic units and soil association. MicroLEIS system was employed to define soil suitability classes to olives, peach, wheat, beans, and sunflower crops. An intelligent module will be added to analyze the digital maps, interact the given data with learning tool (layer) to provide the decision makers with suggested solution not only information. The results showed that the soils are generally characterized by the presence of Calcic, Petrogypsic and Salic horizons. The limiting factors found in the piedmont and coastal plains are salinity, soil depth and texture. These factors decrease the suitability classes to be between S2 and S5.It can be concluded that the digital mapping of land resources using Geographic Information System (GIS) and satellite data preserve in the investment spent in soil and other thematic mapping.