气候变化领域集成服务门户(CCPortal): Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh

CCPortal

DOI	10.1016/j.gsf.2020.09.022
	Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh
	Rahman, Mahfuzur; Chen, Ningsheng; Islam, Md Monirul; Dewan, Ashraf; Pourghasemi, Hamid Reza; Washakh, Rana Muhammad Ali; Nepal, Nirdesh; Tian, Shufeng; Faiz, Hamid; Alam, Mehtab; Ahmed, Naveed
通讯作者	Chen, NS (通讯作者)
发表日期	2021
ISSN	1674-9871
卷号	12 期号:3
英文摘要	This work developed models to identify optimal spatial distribution of emergency evacuation centers (EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh. The use of location-allocation models (LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk. In the first step, flood susceptibility maps were developed using machine learning models (MLMs), including: Levenberg-Marquardt back propagation (LM-BP) neural network and decision trees (DT) and multi-criteria decision making (MCDM) method. Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic (AUROC) curve. Mathematical approaches in a geographic information system(GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem (MCLP), the maximize attendance (MA), p-median problem (PMP), and the location set covering problem(LSCP). The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs (i.e., not all demand points could be reached within a 60-min travel time). We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation. (C) 2021 ChinaUniversity of Geosciences (Beijing) and Peking University. Production and hosting by Elsevier B.V.
关键词	MULTICRITERIA DECISION-MAKING SUPPORT VECTOR MACHINE FLOOD HAZARD CLIMATE-CHANGE SUSCEPTIBILITY AREA VULNERABILITY WEIGHTS
英文关键词	Natural disasters; Emergency evacuation centers; Flooding; Machine learning; Multi-criteria decision making; Location-allocation model
语种	英语
WOS研究方向	Geology
WOS类目	Geosciences, Multidisciplinary
WOS记录号	WOS:000636463500013
来源期刊	GEOSCIENCE FRONTIERS
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260507
推荐引用方式 GB/T 7714	Rahman, Mahfuzur,Chen, Ningsheng,Islam, Md Monirul,et al. Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh[J]. 中国科学院青藏高原研究所,2021,12(3).
APA	Rahman, Mahfuzur.,Chen, Ningsheng.,Islam, Md Monirul.,Dewan, Ashraf.,Pourghasemi, Hamid Reza.,...&Ahmed, Naveed.(2021).Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh.GEOSCIENCE FRONTIERS,12(3).
MLA	Rahman, Mahfuzur,et al."Location-allocation modeling for emergency evacuation planning with GIS and remote sensing: A case study of Northeast Bangladesh".GEOSCIENCE FRONTIERS 12.3(2021).