Spatial resolution enhancement of SSM/I data
Abstract
One of the limitations in using Special Sensor Microwave/Imager (SSM/I) data for land and vegetation studies is the relatively low-spatial resolution. To ameliorate this limitation, resolution-enhancement algorithms can be applied to the data. In this paper, the Backus-Gilbert inversion (BGI) technique and the scatterometer image-reconstruction (SIR) algorithm are investigated as possible methods for creating enhanced resolution images from SSM/I data. The two algorithms are compared via both the simulation and the actual SSM/I data. The algorithms offer similar resolution enhancement, though SIR requires significantly less computation. Sample results over two land regions of South America are presented.
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Mixing the two types of sensors into a single CDR would require careful consideration of the mismatch in spatial resolution and possibly advanced enhanced resolution methods, which are not used here.
“Mixing the two types of sensors (coarse resolution with medium resolution) into a single CDR would require careful consideration of the mismatch in spatial resolution and possibly advanced enhanced resolution methods (e.g.Long and Daum, 1998;Long and Brodzik, 2016), which are not used here.”
From Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records (2019) · cites this paper as Long and Daum, 1998
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Version 2 of the EUMETSAT OSI SAF and ESA CCI sea-ice concentration climate data records
Lavergne, T., Sørensen, A. M., Kern, S., Tonboe, R., Notz, D., Aaboe, S., Bell, L., Dybkjær, G., Eastwood, S., Gabarro, C., et al. (2019) · The Cryosphere · doi:10.5194/tc-13-49-2019 · Cited by 469 · see citing works
“Mixing the two types of sensors (coarse resolution with medium resolution) into a single CDR would require careful consideration of the mismatch in spatial resolution and possibly advanced enhanced resolution methods (e.g. Long and Daum, 1998; Long and Brodzik, 2016), which are not used here.”
Method
- Authors
- Long, D. G., & Daum, D. L.
- Affiliations
- Brigham Young University (US)
- ORCID
- Long, D.G.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 1998-03
- Volume
- 36
- Issue
- 2
- Pages
- 407-417
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2137302082
- Cited by
- 163
- References
- 0
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 4 · 2023: 9 · 2022: 14 · 2021: 14 · 2020: 9 · 2019: 11 · 2018: 8 · 2017: 6 · 2016: 11 · 2015: 9 · 2014: 6 · 2013: 6 · 2012: 4
- FWCI
- 4.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Geoscience and Remote Sensing (publishedVersion)
- ScholarsArchive (Brigham Young University) (submittedVersion)
- Topics
- Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
- Physical Sciences › Engineering › Aerospace Engineering › Synthetic Aperture Radar (SAR) Applications and Techniques
- Physical Sciences › Engineering › Biomedical Engineering › Microwave Imaging and Scattering Analysis
- Keywords
- SSM/I, spatial resolution enhancement, Backus-Gilbert inversion, microwave remote sensing, land surface, vegetation, South America
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