Evaluation of Flood Vulnerability of Typical Regions at Dongting Lake Area in China Based on Multi-source Information Digging and Fusion
- DOI
- 10.2991/rac-16.2016.11How to use a DOI?
- Keywords
- Land use/cover change; Flood vulnerability; multi-source information digging and fusion; Dongting Lake area
- Abstract
The flood vulnerability comprehensive evaluation model was established through interpreting the remote sensing image data in 1987, 1998 and 2008 by means of ENVI4.8 and GIS, the collection and analysis to the historical disaster maps and statistical yearbook data of the flood disaster of Dongting Lake area in Hunan Province of China. With the method of analytic hierarchy process ( AHP ) and the percentile to determine the vulnerability parameters of hazard-affected bodies, the influence of land use/cover change on flood vulnerability was studied. The flood vulnerability of typical region of Dongting Lake area was evaluated by means of the flood vulnerability comprehensive evaluation model. The research results show that the vulnerability parameters of hazard-affected bodies is different reflected that the different land use types have different influences on flood vulnerability; The flood vulnerability degree shows obvious spatial distribution ie. the hinterland area in the Dongting Lake area is sensitive to the flood hazard.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Dehua Mao AU - Jinli Wang AU - Xiaohong Fu AU - Jinhui Li PY - 2016/11 DA - 2016/11 TI - Evaluation of Flood Vulnerability of Typical Regions at Dongting Lake Area in China Based on Multi-source Information Digging and Fusion BT - Proceedings of the 7th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention PB - Atlantis Press SP - 65 EP - 76 SN - 1951-6851 UR - https://doi.org/10.2991/rac-16.2016.11 DO - 10.2991/rac-16.2016.11 ID - Mao2016/11 ER -