气候变化领域集成服务门户(CCPortal): Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields

CCPortal

DOI	10.3390/rs13193889
	Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields
	Ma, Chunfeng; Wang, Shuguo; Zhao, Zebin; Ma, Hanqing
通讯作者	Ma, CF (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Heihe Remote Sensing Expt Res Stn, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China.
发表日期	2021
EISSN	2072-4292
卷号	13 期号:19
英文摘要	The release of high-spatiotemporal-resolution Sentinel-1 Synthetic Aperture Radar (SAR) data to the public has provided an unprecedented opportunity to map soil moisture at watershed and agricultural field scales. However, the existing retrieval algorithms fail to derive soil moisture with expected accuracy. Insufficient understanding of the effects of soil and vegetation parameters on the backscatters is an important reason for this failure. To this end, we present a Sensitivity Analysis (SA) to quantify the effects of parameters on the dual-polarized backscatters of Sentinel-1 based on a Water Cloud Model (WCM) and multiple global SA methods. The identification of the incidence angle and polarization of Sentinel-1 and the description scheme of vegetation parameters (A, B and alpha) in WCM are especially emphasized in this analysis towards an optimal estimation of parameters. Multiple SA methods derive identical parameter importance ranks, indicating that a highly reasonable and reliable SA is performed. Comparison between two existing vegetation description schemes shows that the scheme using Vegetation Water Content (VWC) outperforms the scheme combing particle moisture content and VWC. Surface roughness, soil moisture, VWC, and B, are most sensitive on the backscatters. Variation of parameter sensitivity indices with incidence angle at different polarizations indicates that VV- and VH- polarized backscatters at small incidence angles are the optimal options for soil moisture and surface roughness estimation, respectively, while VV-polarized backscatter at larger incidence angles is well-suited for VWC and B estimation and HH-polarized backscatter is well suited for roughness estimation. This analysis improves the understanding of the effects of vegetated surface parameters on multi-angle and multi-polarized backscatters of Sentinel-1 SAR, informing improvement in SAR-based soil moisture retrieval.
关键词	RADAR BACKSCATTERING BAND PARAMETERS RESOLUTION
英文关键词	microwave remote sensing; synthetic aperture radar; global sensitivity analysis; soil moisture
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000717539400001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/253892
作者单位	[Ma, Chunfeng; Zhao, Zebin] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Heihe Remote Sensing Expt Res Stn, Key Lab Remote Sensing Gansu Prov, Lanzhou 730000, Peoples R China; [Wang, Shuguo] Jiangsu Normal Univ, Sch Geog Geomat & Planning, Xuzhou 221116, Jiangsu, Peoples R China; [Ma, Hanqing] Chinese Acad Sci, Lanzhou Informat Ctr, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Ma, Chunfeng,Wang, Shuguo,Zhao, Zebin,et al. Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields[J]. 中国科学院西北生态环境资源研究院,2021,13(19).
APA	Ma, Chunfeng,Wang, Shuguo,Zhao, Zebin,&Ma, Hanqing.(2021).Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields.REMOTE SENSING,13(19).
MLA	Ma, Chunfeng,et al."Global Sensitivity Analysis of a Water Cloud Model toward Soil Moisture Retrieval over Vegetated Agricultural Fields".REMOTE SENSING 13.19(2021).