TY - GEN
T1 - Inverting Soil Moisture from GNSS-R Reflectivity Using a Semi-empirical Model
AU - Zhang, Jiahua
AU - Li, Ming
AU - Braun, John
AU - Weiss, Jan Peter
N1 - Publisher Copyright:
© 2025 USNC-URSI.
PY - 2025
Y1 - 2025
N2 - This study presents an initial investigation in estimating near-surface soil moisture from GNSS reflection signal-based reflectivity observations. A semi-empirical model is implemented firstly under coherent reflection principles, parameterizing reflectivity's interaction with soil moisture, vegetation, and surface roughness. We applied this model to a track of Spire reflection data over Australia to invert soil moisture measurements, which agree well to the collocated SMAP observations with a root mean square difference (RMSD) of 0.05 cm3/cm3. CYGNSS reflectivity observations are used as well to generate gridded maps of soil moisture. Using three-day CYGNSS data over Australia, the resultant averaged soil moisture map depicts a similar spatial variation pattern as SMAP data, with a RMSD of 0.06 cm3/cm3. Our results are promising for using GNSS reflection data to semi-physically invert soil moisture, serving as an independent data source for scientific research and applications.
AB - This study presents an initial investigation in estimating near-surface soil moisture from GNSS reflection signal-based reflectivity observations. A semi-empirical model is implemented firstly under coherent reflection principles, parameterizing reflectivity's interaction with soil moisture, vegetation, and surface roughness. We applied this model to a track of Spire reflection data over Australia to invert soil moisture measurements, which agree well to the collocated SMAP observations with a root mean square difference (RMSD) of 0.05 cm3/cm3. CYGNSS reflectivity observations are used as well to generate gridded maps of soil moisture. Using three-day CYGNSS data over Australia, the resultant averaged soil moisture map depicts a similar spatial variation pattern as SMAP data, with a RMSD of 0.06 cm3/cm3. Our results are promising for using GNSS reflection data to semi-physically invert soil moisture, serving as an independent data source for scientific research and applications.
UR - https://www.scopus.com/pages/publications/105001169311
U2 - 10.23919/USNC-URSINRSM66067.2025.10906839
DO - 10.23919/USNC-URSINRSM66067.2025.10906839
M3 - Conference contribution
AN - SCOPUS:105001169311
T3 - 2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025 - Proceedings
SP - 35
EP - 36
BT - 2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025
Y2 - 7 January 2025 through 10 January 2025
ER -