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Cited by 92Soil Moisture and Remote SensingCalibration and Measurement TechniquesOcean Waves and Remote Sensing

Optimum Image Formation for Spaceborne Microwave Radiometer Products

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Long, David G., Brodzik, Mary J.·2016·IEEE Transactions on Geoscience and Remote Sensing
DOI 10.1109/tgrs.2015.2505677PMC PMC5602580
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Abstract

This paper considers some of the issues of radiometer brightness image formation and reconstruction for use in the NASA-sponsored Calibrated Passive Microwave Daily Equal-Area Scalable Earth Grid 2.0 Brightness Temperature Earth System Data Record project, which generates a multisensor multidecadal time series of high-resolution radiometer products designed to support climate studies. Two primary reconstruction algorithms are considered: the Backus-Gilbert approach and the radiometer form of the scatterometer image reconstruction (SIR) algorithm. These are compared with the conventional drop-in-the-bucket (DIB) gridded image formation approach. Tradeoff study results for the various algorithm options are presented to select optimum values for the grid resolution, the number of SIR iterations, and the BG gamma parameter. We find that although both approaches are effective in improving the spatial resolution of the surface brightness temperature estimates compared to DIB, SIR requires significantly less computation. The sensitivity of the reconstruction to the accuracy of the measurement spatial response function (MRF) is explored. The partial reconstruction of the methods can tolerate errors in the description of the sensor measurement response function, which simplifies the processing of historic sensor data for which the MRF is not known as well as modern sensors. Simulation tradeoff results are confirmed using actual data.

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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 Brodzik, 2016

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Authors
Long, D. G., & Brodzik, M. J.
Affiliations
  • Brigham Young University (US)
  • Cooperative Institute for Research in Environmental Sciences (US)
ORCID
Venue
IEEE Transactions on Geoscience and Remote Sensing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2016-05
Volume
54
Issue
5
Pages
2763-2779
ISSN
  • 0196-2892 (ISSN-L)
  • 1558-0644
DOI
10.1109/tgrs.2015.2505677
PMC
PMC5602580
OpenAlex
W2312680109
Cited by
92
References
0
Citations by year
2026: 4 · 2025: 8 · 2024: 6 · 2023: 7 · 2022: 20 · 2021: 12 · 2020: 10 · 2019: 12 · 2018: 7 · 2017: 3 · 2016: 2 · 2015: 1
FWCI
3.12
Type
journal article
Language
en
Open access
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
Locations
  • IEEE Transactions on Geoscience and Remote Sensing (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
National Aeronautics and Space Administration (NNX13AI28A)
Topics
  • Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
  • Physical Sciences › Engineering › Aerospace Engineering › Calibration and Measurement Techniques
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Ocean Waves and Remote Sensing
Keywords
passive microwave radiometer, brightness temperature, image reconstruction, Backus-Gilbert method, spatial resolution, climate data record, satellite sensors

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