基于gis的加权线性组合分析与遥感技术在约旦马弗拉克市固体废物处置场地选择中的应用

A. A. Hanbali, Bayan Alsaaideh, A. Kondoh
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引用次数: 104

摘要

通过地理信息系统(GIS)、加权线性组合(WLC)分析和遥感技术的集成,确定了约旦马弗拉克市垃圾填埋场的选址。以矢量和栅格GIS格式从各种来源收集了几个参数,然后在基于GIS的WLC分析中使用,以选择最佳的固体废物处置地点。即,在本研究中考虑了城市地区、农业用地、通道、地表含水层、地下水位、断层系统、水井、溪流和土地斜坡。利用1989年、1999年和2009年的Landsat数据监测了研究区内城市扩张的趋势,以支持处置场地的选择过程。研究发现,约84%的研究区域属于“最适宜”至“中等适宜”的堆填区,而其余研究区域则属于“较不适宜”至“不适宜”的堆填区。基于Landsat卫星数据的分析,近30年来城市面积扩大了240%以上,主要向南和西南方向扩展,除了现有处置场址附近的村庄有向东和东北方向扩展的趋势。最后,考虑到基于gis的WLC分析中应用的环境、生物物理和经济变量,提出了三个地点作为现有处置地点的替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using GIS-Based Weighted Linear Combination Analysis and Remote Sensing Techniques to Select Optimum Solid Waste Disposal Sites within Mafraq City, Jordan
Landfill siting was determined within Mafraq City, Jordan, through the integration of geographic information system (GIS), weighted linear combination (WLC) analysis, and remote sensing techniques. Several parameters were collected from various sources in vector and raster GIS formats, and then, used within the GIS-based WLC analysis to select optimum solid waste disposal sites. Namely, urban areas, agricultural lands, access roads, surface aquifers, groundwater table, fault system, water wells, streams, and land slope were considered in this research. Also, the trend of urban expansion within the study area was monitored using the Landsat data of 1989, 1999, and 2009 to support the selection process of disposal sites. It is found that about 84% of the study area was within “most suitable” to “moderately suitable” classes for landfill sites, while the rest of the study area was within “poorly suitable” and “unsuitable” classes. Based on the analysis of Landsat satellite data the urban area was expanded of more than 240% during the last three decades, mainly toward south, and southwest, except the villages near the existing disposal site, where the trend was toward east and northeast. Finally, three sites were suggested as alternatives to the existing disposal site taking into the consideration the environmental, biophysical, and economical variables applied in the GIS-based WLC analysis.
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