Hazard zoning for spatial planning using GIS-based landslide susceptibility assessment: a new hybrid integrated data-driven and knowledge-based model

2019 ◽  
Vol 12 (4) ◽  
Author(s):  
Qadir Ashournejad ◽  
Ali Hosseini ◽  
Biswajeet Pradhan ◽  
Seyed Javad Hosseini
Proceedings ◽  
2019 ◽  
Vol 30 (1) ◽  
pp. 14
Author(s):  
Giacomo Titti ◽  
Lisa Borgatti ◽  
Qiang Zou ◽  
Alessandro Pasuto

One of the prioritized project of the Belt and Road Initiative is the Silk Road Disaster Risk Reduction. The main aim of the project is to investigate natural hazards affecting Central Asia and Europe in order to understand their evolution and support the spatial planning related to the new infrastructures designing prevention and mitigation measures. The landslide susceptibility zoning is a common practice for land-use planning and environmental impact assessment. Considering the susceptibility as part of the hazard zoning work-flow, a multi-scale (multi-Tier) landslide susceptibility assessment has been carried out and the results are illustrated in this work. Starting from the continental (Tier 1) up to the regional analysis (Tier ≥ 2), the most susceptible areas have been defined to be exploited by successive zoning. Once the most susceptible areas at a regional scale are detected, the hazard zoning can be assessed. In the literature, the landslide susceptibility at continental or global scale has seldom been evaluated. The complexity of the analysis is strictly related to the extension of the study area: the smaller the scale, the higher the complexity of the analysis. Moreover, coordination issues between people and local governments, lack of data due to the absence of strategies for hazards and risk mitigation and data heterogeneity significantly affect the results and forces to find new and innovative solutions from the scientific point of view. In this framework, the Tier 1 landslide susceptibility of the southern Asia has been investigated. It represents the first application of the proposed approach. The results reveal a promising prediction capacity of the method which will be applied to the rest of the Belt and Road study area. The limits, and potentialities of a continental landslide susceptibility are here described. The uncertainty which affect the results of the Tier 1 assessment is mainly related to the lack of consistent data, especially, a global and reliable landslide inventory. However, the Tier 1 landslide susceptibility map has the role to give an overview of the entire study area and to provide the definition of the most landslides prone areas. The method adopted for the analysis is statistically-based and all the resources (software, libraries and data) are open-source. In order to support the reproducibility of the results, a new QGIS tool for statistical analysis has been developed. The Weights of Evidence method has been already implemented, whereas other methods will be coded during further activity.


2015 ◽  
Vol 35 ◽  
pp. 25-28 ◽  
Author(s):  
Massimiliano Bordoni ◽  
Maria Giuseppina Persichillo ◽  
Claudia Meisina ◽  
Andrea Cevasco ◽  
Roberto Giannecchini ◽  
...  

2021 ◽  
Author(s):  
Cahio Guimarães Seabra Eiras ◽  
Juliana Ribeiro Gonçalves de Souza ◽  
Renata Delicio Andrade de Freitas ◽  
César Falcão Barella ◽  
Tiago Martins Pereira

Geosciences ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 493 ◽  
Author(s):  
Vincenzo Marsala ◽  
Alberto Galli ◽  
Giorgio Paglia ◽  
Enrico Miccadei

This work is focused on the landslide susceptibility assessment, applied to Mauritius Island. The study area is a volcanic island located in the western part of the Indian Ocean and it is characterized by a plateau-like morphology interrupted by three rugged mountain areas. The island is severely affected by geo-hydrological hazards, generally triggered by tropical storms and cyclones. The landslide susceptibility analysis was performed through an integrated approach based on morphometric analysis and preliminary Geographical Information System (GIS)-based techniques, supported by photogeological analysis and geomorphological field mapping. The analysis was completed following a mixed heuristic and statistical approach, integrated using GIS technology. This approach led to the identification of eight landslide controlling factors. Hence, each factor was evaluated by assigning appropriate expert-based weights and analyzed for the construction of thematic maps. Finally, all the collected data were mapped through a cartographic overlay process in order to realize a new zonation of landslide susceptibility. The resulting map was grouped into four landslide susceptibility classes: low, medium, high, and very high. This work provides a scientific basis that could be effectively applied in other tropical areas showing similar climatic and geomorphological features, in order to develop sustainable territorial planning, emergency management, and loss-reduction measures.


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