Enhancing Soil Moisture Estimates through the Fusion of SMAP and GNSS-R Data at 3-km Resolution for Daily Mapping

Soil moisture; Global navigation satellite system; Land surface; Spatial resolution; Signal resolution; Spaceborne radar; Soil measurements; Sea surface; Reflection; Orbits; global navigation satellite system-reflectometry (GNSS-R); cyclone global navigation satellite system (CYGNSS); Spire Global Inc.; soil moisture active passive (SMAP); bistatic radar; data fusion; high-resolution soil moisture mapping

Abstract :

[en] High-resolution, large-scale near-surface soil moisture information is critical for many hydrology and climate applications, yet traditional radars and radiometers often fall short of providing information at the required spatial and temporal scales. This study proposes a method for fusing Soil Moisture Active Passive (SMAP) data with spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) measurements from the Cyclone GNSS (CYGNSS) and Spire near-nadir GNSS-R missions, generating soil moisture products at 3- and 9-km resolutions. GNSS-R uses L-band signals that are sensitive to changes in biogeophysical parameters, such as soil moisture. A linear regression-based algorithm retrieves soil moisture from both CYGNSS and Spire data, which, despite showing biases relative to one another, exhibit similar sensitivities to soil moisture variations. The 9-km fused product integrates observed and interpolated GNSS-R estimates to complement daily SMAP 9-km maps, while the 3-km product refines GNSS-R retrievals using available SMAP data. This approach is validated against in-situ measurements and the SMAP/Sentinel 3-km product over mainland Australia for 2021. Our findings indicate a median unbiased root-mean-square error (ubRMSE) of 0.049 cm3cm-3 for the 3-km product and 0.054 cm3cm-3 for the 9-km product, both of which are comparable to SMAP's ubRMSE of 0.054 cm3cm-3. The fused products provide daily soil moisture retrievals with accuracy comparable to SMAP while significantly improving temporal resolution. The 3-km product, in particular, captures finer spatial variability, offering a more detailed representation of soil moisture dynamics.

Disciplines :

Earth sciences & physical geography
Space science, astronomy & astrophysics
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Setti, Paulo T.

TABIBI, Sajad ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

External co-authors :

Language :

English

Title :

Enhancing Soil Moisture Estimates through the Fusion of SMAP and GNSS-R Data at 3-km Resolution for Daily Mapping

Publication date :

2025

Journal title :

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

ISSN :

1939-1404

eISSN :

2151-1535

Pages :

1-15

Peer reviewed :

Peer Reviewed verified by ORBi

Focus Area :

Computational Sciences
Sustainable Development

Development Goals :

2. Zero hunger
9. Industry, innovation and infrastructure
13. Climate action

Available on ORBilu :

since 25 January 2025

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