A Merged CYGNSS Soil Moisture Product Using a Minimum Variance Estimator
Data from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission have shown promise for the retrieval of soil moisture, and many soil moisture products using CYGNSS data have been developed. In this work, we present a merged product that combines several CYGNSS soil moisture products using a minimum variance estimator (MVE). The MVE identifies an optimal weighted averaging scheme based on the error covariance characteristics of the CYGNSS soil moisture products. The error covariance matrix is computed using two reference datasets: soil moisture data from the Soil Moisture Active Passive (SMAP) radiometer and in situ soil moisture data. The results from each of these provide insights into both the performance of the merged product and the individual input CYGNSS products. Overall, the merged product offers better performance than any individual CYGNSS product while also offering better temporal resolution than SMAP. The results of this work also demonstrate that the use of the MVE is a compelling technique for soil moisture applications.
Authors
- Paulo T. Setti (ORCID: https://orcid.org/0000-0001-5080-1832)
- Joel T. Johnson (ORCID: https://orcid.org/0000-0002-6921-6059)
- Simon Yueh (ORCID: https://orcid.org/0000-0001-7061-5295)
- Clara Chew (ORCID: https://orcid.org/0000-0001-6979-4396)
- Xiaolan Xu (ORCID: https://orcid.org/0000-0003-4321-7931)
- Jeffrey D. Ouellette (ORCID: https://orcid.org/0000-0003-3718-2509)
- Erik Hodges (ORCID: https://orcid.org/0000-0002-4737-163X)
- Sajad Tabibi (ORCID: https://orcid.org/0000-0003-0913-9597)
- Mohammad M. Al-Khaldi (ORCID: https://orcid.org/0000-0003-2478-5909)
- Volkan Senyurek (ORCID: https://orcid.org/0000-0003-4446-4977)
- Ali Cafer Gürbüz (ORCID: https://orcid.org/0000-0001-8923-0299)
- Dinan Bai (ORCID: https://orcid.org/0009-0009-6500-4372)
- S. Pettinato (ORCID: https://orcid.org/0000-0002-3155-8918)
- Mahta Moghaddam (ORCID: https://orcid.org/0000-0001-5304-2616)
- Rashmi Shah (ORCID: https://orcid.org/0000-0002-5412-9358)
- Mehmet Kurum (ORCID: https://orcid.org/0000-0002-5750-9014)
- M M Nabi (ORCID: https://orcid.org/0000-0001-5910-2501)
- Christopher S. Ruf (ORCID: https://orcid.org/0000-0002-5937-4483)
- Eric E. Small (ORCID: https://orcid.org/0000-0002-5010-4954)
- E. Santi (ORCID: https://orcid.org/0000-0003-1882-6321)
- Fangni Lei (ORCID: https://orcid.org/0000-0002-0201-7717)
- Akiko Hayashi
Institutions
- University of Southern California (US)
- United States Naval Research Laboratory (US)
- Jet Propulsion Laboratory (US)
- North Carolina State University (US)
- University of Georgia (US)
- University of Luxembourg (LU)
- University of Colorado Boulder (US)
- Hydrologic Research Center (US)
- Department of Space (IN)
- Sensors (United States) (US)
- Center For Remote Sensing (United States) (US)
- National Research Council (IT)
- The Ohio State University (US)
- Western Kentucky University (US)
- Mississippi State University (US)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3597532
- Citations
- 2
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 1.60
Funders
- NASA Headquarters