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Multi-criteria risk evaluation by integrating an analytical network process approach into GIS-based sensitivity and uncertainty analyses

机译:通过将分析网络过程方法集成到基于GIS的敏感性和不确定性分析中,进行多标准风险评估

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ABSTRACT Geographic information system (GIS)-based multi-criteria decision analysis (MCDA) is commonly used to solve a range of complex spatial problems. We have incorporated an analytical network process (ANP) as a central part of MCDA and used this approach for land subsidence susceptibility mapping (LSSM). We used an ANP approach in combination with the concepts of global sensitivity and uncertainty analyses, in order to minimize any associated errors. This approach was tested for a LSSM application in north-western Iran, using a methodology that consisted of three distinct phases. An ANP approach was used in the first phase to derive criteria weightings by analysing relevant criteria, which included topographic, hydrologic, climatologic, geological, and anthropological indicators. The second phase involved evaluating the uncertainty and sensitivity of areas susceptible to subsidence as a function of the derived weightings, using Monte Carlo simulations. The third phase then used a land subsidence inventory database to validate the results and to measure any improvement in accuracy following sensitivity analysis. Results indicated a 6% improvement in the accuracy of the ANP method as a result of using an integrated global sensitivity analysis.
机译:摘要基于地理信息系统(GIS)的多标准决策分析(MCDA)通常用于解决一系列复杂的空间问题。我们已将分析网络过程(ANP)纳入了MCDA的核心部分,并将此方法用于土地沉降敏感性图(LSSM)。我们将ANP方法与全局敏感性和不确定性分析的概念结合使用,以最大程度地减少任何相关的误差。使用由三个不同阶段组成的方法,对该方法在伊朗西北部的LSSM应用程序中进行了测试。第一阶段使用ANP方法通过分析相关标准(包括地形,水文,气候,地质和人类学指标)得出标准权重。第二阶段涉及使用蒙特卡罗模拟评估易陷下区域的不确定性和敏感度,并将其作为导出权重的函数。然后,第三阶段使用地面沉降清单数据库来验证结果并测量敏感性分析后准确性的任何提高。结果表明,通过使用集成的全局灵敏度分析,ANP方法的准确性提高了6%。

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