中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

文献类型:期刊论文

作者Hao, Cui1; Zhang, Jiahua1; Yao, Fengmei1
刊名INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
出版日期2015
卷号35页码:507-511
关键词Optimized meteorological drought index (OMDI) Optimized vegetation drought index (OVDI) Drought Standardized precipitation evapotranspiration index (SPEI) Multi-source satellites data Southwest China
通讯作者Zhang, JH (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Lab Digital Earth Sci, Beijing 100094, Peoples R China.
英文摘要Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area. (C) 2014 Elsevier B.V. All rights reserved.
研究领域[WOS]Remote Sensing
收录类别SCI
语种英语
WOS记录号WOS:000347577400012
源URL[http://ir.ceode.ac.cn/handle/183411/38480]  
专题遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位1.[Hao, Cui] Chinese Acad Meteorol Sci, Lab Remote Sensing & Climate Informat, Beijing 100081, Peoples R China
2.[Zhang, Jiahua] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Lab Digital Earth Sci, Beijing 100094, Peoples R China
3.[Yao, Fengmei] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Hao, Cui,Zhang, Jiahua,Yao, Fengmei. Combination of multi-sensor remote sensing data for drought monitoring over Southwest China[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2015,35:507-511.
APA Hao, Cui,Zhang, Jiahua,&Yao, Fengmei.(2015).Combination of multi-sensor remote sensing data for drought monitoring over Southwest China.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,35,507-511.
MLA Hao, Cui,et al."Combination of multi-sensor remote sensing data for drought monitoring over Southwest China".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 35(2015):507-511.

入库方式: OAI收割

来源:遥感与数字地球研究所

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