气候变化领域集成服务门户(CCPortal): Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data

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DOI	10.1016/j.rse.2020.111944
	Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data
	Yan Q.; Huang W.; Jin S.; Jia Y.
发表日期	2020
ISSN	00344257
卷号	247
英文摘要	In this paper, an effective schematic is developed for estimating soil moisture (SM) from CYclone Global Navigation Satellite System (CYGNSS) data. Here, a three-layer model of air, vegetation cover, and soil is considered. In practice, the surface reflectivity (Γ) along with its statistics derived from the CYGNSS data and the ancillary vegetation opacity (τ) data from Soil Moisture Active Passive (SMAP) are employed. The expression for empirically retrieving SM from τ, Γ and its corresponding statistics are determined through the linear regression technique. The CYGNSS data collected over the land surfaces within ±37° (latitude) during the whole year of 2018 are investigated. The reference SM data are obtained from SMAP, and are regarded as ground-truth in this work. Validation and assessment are performed on the pan-tropical daily data collected throughout the annual circle at a resolution of 36 × 36 km2. Experimental evaluation demonstrates good consistency between the SM derived from CYGNSS data and the ground-truth, with a correlation coefficient of 0.80 and a root-mean-square error of 0.07 cm3/cm3. This method succeeds in providing SM estimations on a pan-tropical scale that does not rely on ongoing knowledge of SM and merely employs the least ancillary data. Furthermore, the intense temporal and spatial coverages of CYGNSS SM results are also illustrated. The use of CYGNSS SM significantly enhances the pan-tropical coverage of SMAP SM by about 22% on average. The satisfactory outcomes achieved here prove CYGNSS as an efficient complementary tool for pan-tropical SM sensing on a daily basis. © 2020 Elsevier Inc.
英文关键词	CYGNSS; GNSS-Reflectometry; SMAP; Soil moisture
语种	英语
scopus关键词	Global positioning system; Mean square error; Soil moisture; Storms; Tropics; Vegetation; Correlation coefficient; Experimental evaluation; Global Navigation Satellite Systems; Linear regression techniques; Root mean square errors; Soil moisture active passive (SMAP); Surface reflectivity; Temporal and spatial; Soil surveys; land surface; mapping method; satellite data; soil moisture; surface reflectance; three-dimensional modeling
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179230
作者单位	School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Faculty of Engineering and Applied Science, Memorial University, St. John's, NL A1B 3X5, Canada; Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, 200030, China; Department of Surveying and Geoinformatics, Nanjing University of Posts and Telecommunications, Nanjing, 210023, China
推荐引用方式 GB/T 7714	Yan Q.,Huang W.,Jin S.,et al. Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data[J],2020,247.
APA	Yan Q.,Huang W.,Jin S.,&Jia Y..(2020).Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data.Remote Sensing of Environment,247.
MLA	Yan Q.,et al."Pan-tropical soil moisture mapping based on a three-layer model from CYGNSS GNSS-R data".Remote Sensing of Environment 247(2020).