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Time-Series Retrieval of Soil Moisture Using CYGNSS

Al-Khaldi, Mohammad M., Johnson, Joel T., O'Brien, Andrew J., Balenzano, Anna, Mattia, Francesco·2019·IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/tgrs.2018.2890646
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Abstract

Time-series retrievals of soil moisture obtained from the Cyclone Global Navigation Satellite System (CYGNSS) constellation are presented. The retrieval approach assumes that vegetation and roughness changes occur on timescales longer than those associated with soil moisture changes to allow soil moisture sensing in the presence of vegetation and surface roughness contributions as well as the varying incidence angles associated with spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) systems. The approach is focused on incoherent scattering from land surfaces due to the expectation that coherent land surface returns arise primarily from inland water body contributions that are not directly representative of soil moisture. An approach for discarding coherent CYGNSS measurements is therefore developed and described. Because the approach requires the retrieval of N temporal soil moisture samples at a given location but uses only N-1 ratios of CYGNSS measured quantities, ancillary information is incorporated in the retrieval through the use of maximum and minimum monthly soil moisture maps obtained from the Soil Moisture Active Passive (SMAP) mission. Retrieved soil moistures are presented for the 6-month period December 2017-May 2018 and are compared against values reported by the SMAP mission. The comparisons suggest that there exists the potential for using spaceborne GNSS-R systems for global soil moisture retrievals with an rms error on the order of 0.04 cm3…

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    From Characterization of River Width Measurement Capability by Space Borne GNSS-Reflectometry (2024) · cites this paper as [6]

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Research works printed but not linked: 41

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Metadata

Authors
Al-Khaldi, M. M., Johnson, J. T., O'Brien, A. J., Balenzano, A., & Mattia, F.
ORCID
Venue
IEEE Transactions on Geoscience and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2019-07
Volume
57
Issue
7
Pages
4322-4331
ISSN
  • 0196-2892
  • 1558-0644
DOI
10.1109/tgrs.2018.2890646
Cited by
234
References
0
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