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Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China
Feng, Xiaoming1,2; Li, Jiaxing1,3; Cheng, Wei1,4; Fu, Bojie1,2; Wang, Yunqiang5,6,7; Lu, Yihe1,2; Shao, Ming'an7
2017-07-01
发表期刊REMOTE SENSING OF ENVIRONMENT
卷号196期号:2017页码:253-264
文章类型Article
摘要Knowledge of soil moisture, however varied in space and time, is critical for planning land use in water-limited drylands. Although satellite observations provide soil moisture instantaneously at large scale, few studies have addressed the application of satellite soil moisture retrieval in dryland areas with changing land use. In this study, we propose a method to evaluate the spatiotemporal variance of satellite retrieval based on the evaluation of soil moisture retrievals from the Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E). The operation period of this instrument (June 2002 to October 2011) covers the re-vegetation of the semi-arid Loess Plateau. Our study found that AMSR-E retrievals posted by the Japanese Aerospace Exploration Agency (JAXA) capture the spatiotemporal variance of soil moisture in the Loess Plateau, as well as the in-situ measured soil moisture decrease following the massive re-vegetation-despite it differing from the in-situ measurement in spatial scale. Soil moisture decrease in response to the massive re-vegetation occurred in a transition zone of grass-forest ecosystems with annual precipitation between 450 and 550 mm. Our study suggests that current AMSR-E JAXA retrievals are an essential alternative to field measurement and model simulation, because they can identify the location and spatial extent of areas where soil moisture is sensitive to climate change and managed re-vegetation. To avoid the overconsumption of soil water and limited plant growth in transition zone, managers of dryland areas should pay special attention to species selection. (C) 2017 Elsevier Inc. All rights reserved.
关键词Amsr-e Loess Plateau Precipitation Gradient Re-vegetation Soil Moisture
WOS标题词Science & Technology ; Life Sciences & Biomedicine ; Technology
DOI10.1016/j.rse.2017.05.012
关键词[WOS]IN-SITU OBSERVATIONS ; REMOTE-SENSING DATA ; WATER CONTENT ; SURFACE-TEMPERATURE ; HILLSLOPE SCALE ; TIBETAN PLATEAU ; CATCHMENT SCALE ; HIGH-RESOLUTION ; SATELLITE DATA ; INDEX SPACE
收录类别SCI
语种英语
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号WOS:000403443700019
引用统计
被引频次:7[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ieecas.cn/handle/361006/5460
专题生态环境研究室
作者单位1.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, POB 2871, Beijing 100085, Peoples R China
2.Joint Ctr Global Change Studies, Beijing 100875, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Univ Sci & Technol China, Sch Life Sci, Hefei 230026, Anhui, Peoples R China
5.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Shaanxi, Peoples R China
6.Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Peoples R China
7.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
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Feng, Xiaoming,Li, Jiaxing,Cheng, Wei,et al. Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China[J]. REMOTE SENSING OF ENVIRONMENT,2017,196(2017):253-264.
APA Feng, Xiaoming.,Li, Jiaxing.,Cheng, Wei.,Fu, Bojie.,Wang, Yunqiang.,...&Shao, Ming'an.(2017).Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China.REMOTE SENSING OF ENVIRONMENT,196(2017),253-264.
MLA Feng, Xiaoming,et al."Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China".REMOTE SENSING OF ENVIRONMENT 196.2017(2017):253-264.
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