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Fuzzy Based Detection of Desertification-prone Areas: A Case Study in Khorasan-Razavi Province, Iran

机译:基于模糊的沙漠化高发区探测:以伊朗霍拉桑-拉扎维省为例

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In this article, a desertification susceptibility map was developed over Khorasan Razavi ecoregions located in northeastern Iran with arid and semi-arid environments. For this purpose, a fuzzy algorithm regarding Dempster-Shafer theory was applied based on six main indicators including wind erosion, aridity severity, soil erodibility, landuse type, salinization and vegetation cover density chosen by Delphi techniques. The indicators were combined under linear fuzzy function and gained to a membership function for each layer. The results indicated about 43.5 % region is susceptible to soil erodibility; also cold hyper-arid and ultra-cold arid deserts ecoregions show a high range of sustainability to desertification.
机译:在本文中,在伊朗东北,干旱和半干旱环境下的霍拉桑·拉扎维(Khorasan Razavi)生态区上绘制了沙漠化敏感性图。为此,基于Delphi技术选择的六个主要指标,包括风蚀,干旱严重程度,土壤易蚀性,土地利用类型,盐渍化和植被覆盖密度,应用了基于Dempster-Shafer理论的模糊算法。指标在线性模糊函数下合并,并获得每一层的隶属函数。结果表明,约43.5%的区域易受土壤侵蚀。寒冷的高干旱和超冷的干旱沙漠生态区也显示出沙漠化的高度可持续性。

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