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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


Published: May 18, 2022
Keywords:
Landslides GIS Geodatabase MCDA LSA
Constantinos Nefros
https://orcid.org/0000-0002-2075-4112
Constantinos Loupasakis
https://orcid.org/0000-0003-1822-6510
Abstract

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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