GIS-Based Risk Assessment and Regionalization of Drought Hazards in China

Based on the monthly precipitation (1960 -2009 ) of China and associated regional socio-economie data, the spatial and temporal pattern of drought in China was assessed by applying a conceptual framework of disaster system theory, which used the hazard and vulnerability as two variables to define th...

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Published in东华大学学报(英文版) Vol. 29; no. 6; pp. 455 - 460
Main Author 张峰 黄敬峰 张丽文 王秀珍
Format Journal Article
LanguageEnglish
Published Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China 2012
Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310058, China%Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China
Key Laboratory of Environmental Remediation and Ecological Health, Ministry of Education, Zhejiang University, Hangzhou 310058, China%Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China
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ISSN1672-5220

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Abstract Based on the monthly precipitation (1960 -2009 ) of China and associated regional socio-economie data, the spatial and temporal pattern of drought in China was assessed by applying a conceptual framework of disaster system theory, which used the hazard and vulnerability as two variables to define the risk of drought. Sichuan province suffered from the severe risk of drought, while Guangxi, Yunnan, Guizhou provinces, and Chongqing city could be classified as the moderate drought risk area of China. Additionally, Tibet plateau in the Northwest of China had the lowest risk of drought. The integrated data from this result provided the valuable information to cope with the drought in respect of optimization utilization of ]!and resources at the regional scale.
AbstractList Based on the monthly precipitation (1960 -2009 ) of China and associated regional socio-economie data, the spatial and temporal pattern of drought in China was assessed by applying a conceptual framework of disaster system theory, which used the hazard and vulnerability as two variables to define the risk of drought. Sichuan province suffered from the severe risk of drought, while Guangxi, Yunnan, Guizhou provinces, and Chongqing city could be classified as the moderate drought risk area of China. Additionally, Tibet plateau in the Northwest of China had the lowest risk of drought. The integrated data from this result provided the valuable information to cope with the drought in respect of optimization utilization of ]!and resources at the regional scale.
Author 张峰 黄敬峰 张丽文 王秀珍
AuthorAffiliation Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310058, China Key Laboratory of Er!vironmental Remediation and Ecological I-lealth, l~inistry of Education, ~Zhejiang University, Hangzhou~I0058 , China Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China
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vulnerability
drought
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geographical information system(GIS)
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drought; hazard; vulnerability ; risk; geographicalinformation system(GIS) ; China
Based on the monthly precipitation (1960 -2009 ) of China and associated regional socio-economie data, the spatial and temporal pattern of drought in China was assessed by applying a conceptual framework of disaster system theory, which used the hazard and vulnerability as two variables to define the risk of drought. Sichuan province suffered from the severe risk of drought, while Guangxi, Yunnan, Guizhou provinces, and Chongqing city could be classified as the moderate drought risk area of China. Additionally, Tibet plateau in the Northwest of China had the lowest risk of drought. The integrated data from this result provided the valuable information to cope with the drought in respect of optimization utilization of ]!and resources at the regional scale.
ZHANG Feng , HUNAG Jing-feng, ZHANG Li-wen, WANG Xiu-zhen 4. 1 Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China 2 Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310058, China 3 Key Laboratory of Er!vironmental Remediation and Ecological Health, Ministry of Education, Zhejiang University, Hangzhou 310058, China 4 Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Hangzhou 311121, China
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Key Laboratory of Agricultural Remote Sensing and Information System, Zhejiang University, Hangzhou 310058, China%Institute of Agricultural Remote Sensing & Information Application, Zhejiang University, Hangzhou 310058, China
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