引入地理空间数据库和地理信息系统技术,作为多准则决策分析方法在滑坡易感性评估中的决策工具

C. Nefros, C. Loupasakis
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引用次数: 3

摘要

每年,世界各地的山体滑坡都会造成许多人死亡,并摧毁许多基础设施。由于其灾难性的结果,科学研究进行了,在持续的基础上,试图确定控制和触发因素,并评估其贡献权重的现象。在这个方向上,许多这些研究使用多标准决策分析方法,因为它们非常有效,可以很快应用。然而,在使用这些方法的新研究中,很大一部分通常用于分析许多先前的研究并验证其结果,这通常会导致严重的延误并需要大量资源。本研究对过去82项相关研究进行了评价,并将其结果整合到全球地理空间数据库中,以展示其作为滑坡易感性评估决策工具的潜力。由于在地理信息系统环境中,其统计和空间相关性与所研究区域的主要参数的结果可以提供关键的指示- -向研究人员提出建议,以及多标准决策分析方法的适用性,其中包括使用其他专家的知识和经验,快速识别最关键的滑坡成因并初步评估其贡献权重。这些迹象显著加快了整个过程,并减少了可能导致整个方法无效的有偏差结论的风险。此外,本研究还强调了地理数据库在整合外部空间数据库的开放获取数据并在滑坡易感性评估过程中使用这些数据的潜力。
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Introducing a geospatial database and GIS techniques as a decision-making tool for multicriteria decision analysis methods in landslides susceptibility assessment
Every year landslides cause many fatalities and destroy numerous infrastructures around the world. Due to their catastrophic results, scientific research studies are conducted, on a continuous basis, trying to determine the controlling and triggering factors, and to evaluate their contribution-weight to that phenomenon. In this direction, many of these studies use multicriteria decision analysis methods as they are quite effective and can be applied rather quickly. However, a large percentage of the new studies that use these methods, is usually devoted to the analysis of many previous research studies and the validation of their results, which usually leads to serious delays and requires significant resources. In this research, 82 relevant past studies are evaluated, and their results are integrated into a worldwide geospatial database, to present its potential as a decision-making tool, during the landslide susceptibility assessment. As it is revealed the results of its statistical and spatial correlation with the examined region’s prevailing parameters in a geographical information system environment, can provide critical indications- suggestions to a researcher and along with the applicability of the multicriteria decision analysis methods, that contain the use of other experts’ knowledge and experience, to lead to the rapid identification of the most critical landslide causal factors and the initial evaluation of their contribution-weight. These indications accelerate significant the whole process and reduce the risk for possible biased conclusions, which can render the whole method ineffective. Moreover, this study highlights the geodatabase’s potential to incorporate open-access data, from external spatial databases and to use them, during the process of the landslide susceptibility assessment.
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