Soil Moisture Retrievals Using CYGNSS Data in a Time-Series Ratio Method: Progress Update and Error Analysis

被引：13

作者：

Al-Khaldi, Mohammad M. ^{[1
]}

Johnson, Joel T. ^{[2
,3
]}

机构：

[1] Univ Corp Atmospher Res UCAR, Constellat Observing Syst Meteorol Ionosphere & C, Boulder, CO 80301 USA

[2] Ohio State Univ, Dept Elect & Comp Engn, Columbus, OH 43210 USA

[3] Ohio State Univ, ElectroSci Lab, Columbus, OH 43210 USA

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2022年 / 19卷

关键词：

Bistatic radar systems; cyclone global navigation satellite system (CYGNSS); global navigation satellite systems reflectometry (GNSS-R); remote sensing; soil moisture; time-series algorithms;

D O I：

10.1109/LGRS.2021.3086092

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

A previously reported time-series ratio method for retrieving soil moisture information from Cyclone Global Navigation Satellite System (CYGNSS) measurements is updated to improve the algorithm used for excluding CYGNSS measurements from the time series, thereby improving the algorithm's computational efficiency while eliminating the requirement for contemporary soil moisture information from Soil Moisture Active Passive (SMAP). Daily CYGNSS soil moisture estimates are retrieved and presented on a 36-km grid over the 27-month period January 2018-May 2020 and show an overall root mean square error approximate to 4.46%, an overall correlation for all attempted retrievals of approximate to 80.53%, and an average correlation for individual pixels of 48.61% relative to SMAP using the updated time-series algorithm. An analysis of the errors of the updated algorithm is also provided as a function of surface properties.

引用

页数：5

共 22 条

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