Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China

doi:10.1016/j.rse.2017.05.012

	Evaluation of AMSR-E retrieval by detecting soil moisture decrease following massive dryland re-vegetation in the Loess Plateau, China
	Shao, Ming'an 1; Lu, Yihe 6,7; Wang, Yunqiang 1,2,3; Fu, Bojie 6,7; Cheng, Wei 4,7; Li, Jiaxing 5,7; Feng, Xiaoming 6,7
刊名	REMOTE SENSING OF ENVIRONMENT
	2017-07-01
卷号	196 期号:2017 页码:253-264
关键词	Amsr-e Loess Plateau Precipitation Gradient Re-vegetation Soil Moisture
DOI	10.1016/j.rse.2017.05.012
文献子类	Article
英文摘要	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.
WOS关键词	IN-SITU OBSERVATIONS ; REMOTE-SENSING DATA ; WATER CONTENT ; SURFACE-TEMPERATURE ; HILLSLOPE SCALE ; TIBETAN PLATEAU ; CATCHMENT SCALE ; HIGH-RESOLUTION ; SATELLITE DATA ; INDEX SPACE
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
WOS记录号	WOS:000403443700019
内容类型	期刊论文
源URL	[http://ir.ieecas.cn/handle/361006/5460]
专题	地球环境研究所_生态环境研究室
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 2.Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Peoples R China 3.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Shaanxi, Peoples R China 4.Univ Sci & Technol China, Sch Life Sci, Hefei 230026, Anhui, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Joint Ctr Global Change Studies, Beijing 100875, Peoples R China 7.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, POB 2871, Beijing 100085, Peoples R China
推荐引用方式 GB/T 7714	Shao, Ming'an,Lu, Yihe,Wang, Yunqiang,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	Shao, Ming'an.,Lu, Yihe.,Wang, Yunqiang.,Fu, Bojie.,Cheng, Wei.,...&Feng, Xiaoming.(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	Shao, Ming'an,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.