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利用遥感和地理信息系统技术绘制土耳其加济安泰普省卡尔塔尔卡亚大坝流域的侵蚀风险图。

Using the Remote Sensing and GIS Technology for Erosion Risk Mapping of Kartalkaya Dam Watershed in Kahramanmaras, Turkey.

作者信息

Yuksel Alaaddin, Gundogan Recep, Akay Abdullah E

机构信息

Kahramanmaras Sutcu Imam University, Faculty of Forestry , Department of Forest Engineering, 46060, Kahramanmaras, Turkey.

Kahramanmaras Sutcu Imam University, Faculty of Agriculture, Department of Soil Science, 46060, Kahramanmaras, Turkey.

出版信息

Sensors (Basel). 2008 Aug 21;8(8):4851-4865. doi: 10.3390/s8084851.

Abstract

The soil erosion is the most serious environmental problem in watershed areas in Turkey. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to develop adequate erosion prevention measures in the watersheds of dams, erosion risk maps should be generated considering these factors. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used for erosion risk mapping in Kartalkaya Dam Watershed of Kahramanmaras, Turkey, based on the methodology implemented in COoRdination of INformation on the Environment (CORINE) model. ASTER imagery was used to generate a land use/cover classification in ERDAS Imagine. The digital maps of the other factors (topography, soil types, and climate) were generated in ArcGIS v9.2, and were then integrated as CORINE input files to produce erosion risk maps. The results indicate that 33.82%, 35.44%, and 30.74% of the study area were under low, moderate, and high actual erosion risks, respectively. The CORINE model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion risk maps in Turkey.

摘要

土壤侵蚀是土耳其流域地区最严重的环境问题。影响土壤侵蚀量的主要因素包括植被覆盖、地形、土壤和气候。为了描述土壤侵蚀风险高的区域,并在大坝流域制定适当的侵蚀预防措施,应考虑这些因素生成侵蚀风险图。基于环境信息协调(CORINE)模型实施的方法,利用遥感(RS)和地理信息系统(GIS)技术对土耳其哈兰马拉斯省卡尔塔尔卡亚大坝流域进行侵蚀风险制图。在ERDAS Imagine中使用ASTER影像生成土地利用/覆盖分类。在ArcGIS v9.2中生成其他因素(地形、土壤类型和气候)的数字地图,然后将其作为CORINE输入文件进行整合,以生成侵蚀风险图。结果表明,研究区域分别有33.82%、35.44%和30.74%处于低、中和高实际侵蚀风险之下。与RS和GIS技术相结合的CORINE模型在土耳其生成准确且成本低廉的侵蚀风险图方面具有巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/721a/3705475/d60fb7c5b43e/sensors-08-04851f1.jpg

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