DocumentCode :
2707515
Title :
An improved model of regional flood disaster risk assessment based on remote sensing data
Author :
Duan, Guangyao ; Zhao, Wenji ; Hu, Zhuowei ; Fang, Dan
Author_Institution :
Beijing Municipal Key Lab. of Resources Environ. & GIS, Capital Normal Univ., Beijing, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
1
Lastpage :
6
Abstract :
This paper puts forward a method to improve the traditional model of regional flood risk assessment with real-time remote sensing monitoring data and historical flood disaster data. It takes the Songhuajiang River Basin as the study area to build the improved regional flood risk assessment model. According to the characteristics of the study area, factors such as rainfall, topography, water density, population density and GDP are selected to build the regional flood risk assessment model based on GIS and AHP, by which the initial Flood Risk Index of Songhuajiang River can be calculated. The historical flood level distribution data that reflect the spatial distribution and frequency of flood events in the study area can be used to improve the hazard index. And with the real-time remote sensing data, the real-time flood extent data can be extracted to improve final risk assessment which reflects the regional flood risk better.
Keywords :
disasters; floods; geographic information systems; rain; remote sensing; risk management; rivers; topography (Earth); AHP; China; GDP; GIS; Songhuajiang river basin; flood risk index; historical flood disaster data; historical flood level distribution data; population density; rainfall; real time remote sensing monitoring data; regional flood disaster risk assessment; regional flood risk assessment model; topography; water density; Data models; Floods; Indexes; Remote sensing; Risk management; Rivers; flood risk assessment; historical disaster data; remote sensing data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics, 2011 19th International Conference on
Conference_Location :
Shanghai
ISSN :
2161-024X
Print_ISBN :
978-1-61284-849-5
Type :
conf
DOI :
10.1109/GeoInformatics.2011.5980776
Filename :
5980776
Link To Document :
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