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Integrating remote sensing with GIS-based multi-criteria evaluation approach for Karst rocky desertification assessment in Southwest of China

机译:遥感与基于GIS的多标准评价方法相结合的西南喀斯特石漠化评价

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摘要

The increasing exploitation of Karst resources is leading to severe environmental impacts, as Karst frequently occurs in the most fragile and vulnerable environments. This paper presents a multi-criteria evaluation (MCE) approach in a spatial context to support Karst rocky desertification (KRD) assessment by integrating remote sensing data with GIS. The study area is located in Wenshan Prefecture, Yunnan Province, Southwest of China. Criteria and impact factors for KRD first were identified and weighted through pairwise comparison method. A GIS fuzzy set membership function was then used to generate gradient effects of each criterion, and a clustering method based on K-mean algorithms was used to classify KRD into several descending rank zones (or levels). Both ROC and error matrix assessments indicated that the MCE approach is better than the NDVI approach. In addition, we found it is useful to integrate the topographic and human disturbance factors into KRD mapping and assessment, compared with most of the previous KRD assessment studies mainly focused on developing vegetation or land cover information in karst regions by using remote sensing alone. Furthermore, the integrated MCE approach is robust, flexible, and easy to be implemented. It also explicitly includes the quantitative and qualitative information, for instance, opinions of decision makers and experts as well as characteristics of the landscape.
机译:由于岩溶经常发生在最脆弱和最脆弱的环境中,岩溶资源的日益开发正在导致严重的环境影响。本文提出了一种在空间环境下通过将遥感数据与GIS集成来支持喀斯特石漠化(KRD)评估的多标准评估(MCE)方法。研究区域位于中国西南部云南省文山州。首先确定了KRD的标准和影响因素,并通过成对比较法加权。然后使用GIS模糊集隶属函数生成每个准则的梯度效果,并使用基于K均值算法的聚类方法将KRD划分为几个降序区域(或级别)。 ROC和误差矩阵评估均表明,MCE方法优于NDVI方法。此外,我们发现将地形和人为干扰因素整合到KRD测绘和评估中是有用的,而以前的大多数KRD评估研究主要侧重于仅通过遥感来发展喀斯特地区的植被或土地覆盖信息。此外,集成的MCE方法是可靠,灵活且易于实施的。它还明确包括定量和定性信息,例如决策者和专家的意见以及景观特征。

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