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Mapping Inland Surface Water with Spaceborne GNSS Reflectometry and SAR

Downs, Brandi
http://orcid.org/0000-0001-5569-7560
http://rave.ohiolink.edu/etdc/view?acc_num=osu1689775689250236

Abstract Details

2023, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.
Observing dynamic changes in the Earth’s surface water is crucial for understanding and modeling the global hydrological cycle. Rapid changes in surface water, such as flooding and wetland inundation, are some of the most important events, yet quantitative observations of these events are among the most challenging to acquire. Current satellite-based flood and wetland inundation products are largely based on optical remote sensing methods, which exhibit limited ability to detect surface water through rain, clouds, and vegetation. While current satellite microwave remote sensing using radar can overcome some of these limitations, these instruments are on single satellite platforms and may overpass regions on multi-week timescales, missing flash flooding and dynamic inundation events. Recently, a novel remote sensing technique known as Global Navigation Satellite System Reflectometry (GNSS-R) has shown great potential in the detection of terrestrial surface water beneath clouds and vegetation. NASA’s Cyclone Global Navigation Satellite System (CYGNSS) mission is a small satellite constellation using GNSS-R instruments that receive reflections of L-band GPS signals known to penetrate rain, clouds, and vegetation, and has a regional sub-daily revisit rate. CYGNSS has recently shown the potential to resolve small-scale and dynamic hydrological features over land, such as rivers, lakes, wetlands, and urban flooding. CYGNSS is an eight-satellite constellation, resulting in sub-daily measurement frequencies that provide a unique opportunity to observe short timescale changes. However, CYGNSS measurements occur in sparse, quasi-random tracks since GPS reflections can occur anywhere in the field of view. This makes understanding the observability of dynamic events more difficult as compared to simpler imaging instruments. Changes in signal-to-noise ratio (SNR) that indicate a dynamic change in the scene are confounded by inherent variability due to other sources, including vegetation, geometry changes, instrument gain calibration, and surface roughness due to wind. Therefore, determining the best methods of applying spaceborne GNSS-R data to map surface water and understanding the associated advantages and limitations are of critical importance. In this work, the performance of spaceborne GNSS-R (specifically CYGNSS) to map inland surface water is evaluated and quantified. Several approaches are developed to help overcome the sparse nature of CYGNSS sampling, including combining measurements with flood models. An algorithm is developed to use electromagnetic models to simulate CYGNSS measurements, compare the simulations with measured data, and retrieve the extent of surface water. An extensive comparison between CYGNSS water maps and those of existing surface water products is also carried out. Finally, a data fusion algorithm commonly used for optical data is modified and extended to the case of GNSS-R and Synthetic Aperture Radar (SAR), leveraging the sub-daily revisit rate of CYGNSS and high spatial resolution of Sentinel-1, enabling short timescale observation of dynamic inundation events in all-weather, day or night conditions, and through vegetation.
Joel Johnson (Advisor)
Lee Potter (Committee Member)
Robert Burkholder (Committee Member)
Andrew O'Brien (Committee Co-Chair)
210 p.
Remote Sensing
remote sensing; hydrology; gnss reflectometry; synthetic aperture radar; data fusion

Recommended Citations

Citations

  • Downs, B. (2023). Mapping Inland Surface Water with Spaceborne GNSS Reflectometry and SAR [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1689775689250236

    APA Style (7th edition)

  • Downs, Brandi. Mapping Inland Surface Water with Spaceborne GNSS Reflectometry and SAR. 2023. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1689775689250236.

    MLA Style (8th edition)

  • Downs, Brandi. "Mapping Inland Surface Water with Spaceborne GNSS Reflectometry and SAR." Doctoral dissertation, Ohio State University, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=osu1689775689250236

    Chicago Manual of Style (17th edition)

osu1689775689250236
66
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This open access ETD is published by The Ohio State University and OhioLINK.