数字土地资源测绘和沿海农业可持续性中的测绘学和智能工具,埃及

Mohamed Zahran, A. Gad
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摘要

埃及西北海岸因其悠久的历史和优美的环境而受到国际社会的关注。在希腊和罗马时期,这个地区被称为面包篮。最近,土地利用的剧烈变化导致许多集水工具遭到破坏,从而降低了农业的重要性。该地区的恢复和自给自足社区的规划需要为这些地区建立一个可持续的土地资源数据库。多概念遥感和地理信息系统(GIS)允许存储、合并和操作大量的专题地图和属性数据。2018年哨兵卫星图像覆盖了埃及西北海岸的研究区域。采用ENVI软件进行图像处理。采用Arc_GIS 10.2系统,以1:5万比例尺的53幅地形图输入与土地资源相关的GIS专题层。实地调查代表了不同的土壤单元并收集了地面控制点。测定了土壤的化学和物理性质,以协助土壤分类。绘制了包括优势地理单元和土壤关联的土壤图谱。采用MicroLEIS系统确定了橄榄、桃、小麦、豆类和向日葵作物的土壤适宜性等级。将增加一个智能模块来分析数字地图,将给定的数据与学习工具(层)交互,为决策者提供建议的解决方案,而不仅仅是信息。结果表明,土壤具有钙质层、岩质层和盐质层的普遍特征。在山前和沿海平原发现的限制因素是盐度、土壤深度和质地。这些因素使适宜性等级降低到S2 ~ S5之间。结果表明,利用地理信息系统(GIS)和卫星数据进行的土地资源数字化制图在土壤和其他专题制图方面的投入较少。
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Geomatics and smart tools in Digital Land Resources Mapping and Sustainability of Coastal Agriculture, Egypt
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.
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