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

dc.contributor.authorBera, Somnath
dc.contributor.authorGnyawali, Kaushal
dc.contributor.authorDahal, Kshitij
dc.contributor.authorMelo, Raquel
dc.contributor.authorLi-Juan, Miao
dc.contributor.authorGuru, Balamurugan
dc.contributor.authorRamana, G V
dc.date.accessioned2022-12-29T16:57:24Z
dc.date.available2022-12-29T16:57:24Z
dc.date.issued2022-11
dc.description.abstractIntense 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 minutes and 60 minutes. This methodology helps develop simultaneous hazard impact plans by local administration units in mountain regions to ensure emergency facilities' safe operation.por
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dc.identifier.authoremailraquel.melo@uevora.pt
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dc.identifier.citationS. Bera, K.R. Gnyawali, K. Dahal, R. Melo, M. Li-Juan, B. Guru, G.V. Ramana, Assessment of shelter location-allocation for multi-hazard emergency evacuation, International Journal of Disaster Risk Reduction (2022), doi: https://doi.org/10.1016/j.ijdrr.2022.103435.por
dc.identifier.doihttps://doi.org/10.1016/j.ijdrr.2022.103435por
dc.identifier.urihttps://www.sciencedirect.com/science/article/abs/pii/S2212420922006549?via%3Dihub
dc.identifier.urihttp://hdl.handle.net/10174/33037
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherELSEVIERpor
dc.rightsrestrictedAccesspor
dc.subjectLandslidespor
dc.subjectFloodspor
dc.subjectPedestrian evacuationpor
dc.subjectShelter location-allocationpor
dc.subjectGoogle Earth Enginepor
dc.subjectRandom Forestpor
dc.titleAssessment of shelter location-allocation for multi-hazard emergency evacuationpor
dc.typearticlepor

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