Assessment of shelter location-allocation for multi-hazard emergency evacuation

• Autor(a) principal: Bera, Somnath
• Data de Publicação: 2022
• Outros Autores: Gnyawali, Kaushal, Dahal, Kshitij, Melo, Raquel, Li-Juan, Miao, Guru, Balamurugan, Ramana, G V
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10451/55311
• topic: Landslides; Floods; Pedestrian evacuation; Shelter location-allocation; Google earth engine; Random fores

Intense rainstorms often trigger multiple disasters in mountain regions, such as floods and landslides. In disaster planning, the local administration allocates nearby schools or open fields as emergency evacuation shelters. However, access to these shelters is often cut off for certain population clusters during disaster impact on routes. We develop a framework for selecting emergency evacuation shelter locations for multi-disaster impact planning (floods and landslides). The framework consists of two parts. Firstly, we develop susceptibility maps of individual hazards using Random Forest algorithm and Google earth engine. Secondly, we assess the shelter's location-allocation by implementing two models in GIS: P-median and maximal covering location problem. Our framework treats existing schools as evacuation shelters and individual households as demand points in an emergency. The P-median method finds the shelter locations by minimizing maximum distances between the households. The maximal covering location problem method evaluates the coverage of households by the facilities of the evacuation shelters within an impedance cutoff. We tested our work in a mountainous village in the Western Ghat region, India, by recreating the 2005 rainstorm disaster that caused more than 190 fatalities and damaged 400 households. The result shows that existing shelters are insufficient to provide services to all households within 30 min and 60 min. This methodology helps develop simultaneous-hazard impact plans by local administration units in mountain regions to ensure emergency facilities' safe operation.