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Evaluation of Spire GNSS-R reflectivity from multiple GNSS constellations for soil moisture estimation.

Authors :
Setti Jr., Paulo T.
Tabibi, Sajad
Source :
International Journal of Remote Sensing; Oct2023, Vol. 44 Issue 20, p6422-6441, 20p
Publication Year :
2023

Abstract

Spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) has emerged as a pivotal tool with different land applications, prominently encompassing soil moisture estimation. In contrast to conventional radiometer satellites commonly used for this purpose, GNSS-R offers higher spatiotemporal coverage while maintaining cost-effectiveness. The potential of using Global Positioning System (GPS) reflections measured by the Cyclone Global Navigation Satellite System (CYGNSS) mission to retrieve soil moisture has been previously demonstrated. In 2019, Spire Global Inc. launched their first GNSS-R satellites, which now comprise a constellation of four CubeSats. These satellites track reflections from multi-constellation, encompassing GPS, Galileo, BeiDou Navigation Satellite System (BDS), and Quasi-Zenith Satellite System (QZSS). In this study, an analysis and validation of Spire GNSS-R L1B surface reflectivity for soil moisture retrieval within east Australia during an eight-month period in 2021 is presented. A comparison of the estimated Spire surface reflectivity to that of CYGNSS is performed, unveiling analogous behavioural patterns and biases across both missions. Soil moisture is estimated using observations from Spire GPS-only, Spire multi-constellation, and CYGNSS. The Soil Moisture Active and Passive (SMAP) retrievals are used as the reference, presuming a linear relationship between changes in soil moisture and changes in reflectivity. Our results indicate that the Spire GNSS-R mission can detect variations in soil moisture with a performance comparable to that of CYGNSS. A median unbiased root-mean-square difference (ubRMSD) of 0.062 m³.m<superscript>-3</superscript> is found for both Spire GPS and multi-constellation when using 9-km products and SMAP as the reference. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01431161
Volume :
44
Issue :
20
Database :
Complementary Index
Journal :
International Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
174188197
Full Text :
https://doi.org/10.1080/01431161.2023.2270108