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solid waste dumping Site Selection Using GIS and Remote Sensing for Kajiado County, Kenya

Journal of Earth Science and Engineering 2014年第11期4卷 693-702页

作者： Titus Mugi Ng'ang'a Wachira Peter Muturi Kimenju John Wangai Wango Tim Joash Ndungu Joseph Matheri Department of Geospatial and Space Technology University ofNairobi Nairobi Kenya School of Biological Sciences University of Nairobi Kenya Department of Plant Science and Crop Protection University of Nairobi Kenya Department of Geomatic and Geospatial Information Systems Jomo Kenyatta University of Science and Technology NairobiKenya Department of Geospatial and Space Technology University of Nairobi Nairobi Kenya

solid waste dumping is a hectic problem in urban and developing areas due to shortage of land for the purpose. The main objective of this study was to select potential areas for suitable solid waste dumping for Kajiado County, Kenya. Eight input map layers including DEM （digital elevation model）, topography, urban settlement, roads, wetlands, rivers, forests and protected areas were prepared and MCDA （Multi Criteria Decision Analysis Methods） were implemented in a GIS （geographic information systems） environment. GIS, RS （remote sensing） and MDCA are powerful tools which can effectively be applied during the planning phase of solid waste management in order to avoid adverse catastrophes in future. The final suitability map was prepared by weighted overlay analyses and leveled as the most suitable, moderate suitable, less suitable and unsuitable areas. The area of each suitability level was calculated using spatial statistics. Polygons representing the most suitable sites were further analyzed in terms of area perimeter ratio in order to investigate the most suitable areas in terms of shape regularity. The leading four polygons considered were marked A, B, C, D respectively in the final map. This study showed that suitable areas for solid waste landfills were limited and scattered in the study area.

关键词： solid waste dumping geographic information system remote sensing multi criteria decision analysis

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