NDLI: Remote Sensing and GIS-Based Flood Vulnerability Assessment in Jiangxi Province in China

Content Provider	IEEE Xplore Digital Library
Author	Ping Chen Xiaoling Chen
Copyright Year	2008
Description	Author affiliation: State Key Lab. of Inf. Eng. in Surveying, Mapping & Remote Sensing, Wuhan Univ., Wuhan (Ping Chen; Xiaoling Chen)
Abstract	Vulnerability assessment acquaints us with degree of risks in global-environmental-change context. Remote sensing (RS) and geographic information system (GIS) is seldom applied to assess comprehensive vulnerability as indispensable socioeconomic factors are hardly expressed by them. Thus we selected counties in Jiangxi Province as study area, calculated vulnerability index VI of them by aggregating sixteen indicators and another index $VI_{RG}$ by aggregating five indicators which could be exactly express by RS and GIS data, and construct exponential formulation between them. Some testing counties were used to check the precision of flood vulnerability categorization by fitted value of VI yielded by exponential formulation between VI and $VI_{RG}.$ Thematic maps of flood vulnerability categorization by VI and fitted value of VI illustrate identical spatial distribution pattern despite existence of wrongly-categorized cases. The overall precision of vulnerability assessment reaches 81.3%. RS and GIS techniques are possible even promising to be applied in comprehensively assessing flood vulnerability.
Starting Page	332
Ending Page	335
File Size	519493
Page Count	4
File Format	PDF
ISBN	9780769535630
DOI	10.1109/ETTandGRS.2008.193
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Geographic Information Systems Economic indicators Laboratories Humans Hazards Floods Environmental economics Remote sensing Indicator Exponential fit GIS Flood vulnerability Precision Vegetation mapping Geoscience and remote sensing
Content Type	Text
Resource Type	Article

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