Mapping Surface Water Extents Using High-rate Coherent Space-borne GNSS-R Measurements

Coherent GNSS reflections over land predominantly occur over surface water bodies. This study presents a method to jointly use carrier phases and signal strengths of reflected signals to identify coherent reflections and applies it to the 50-Hz GNSS-R measurements from Spire Global Cubesats and CYGN...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2022, p.1-1
Main Authors: Zhang, Jiahua, Jade Morton, Y., Wang, Yang, Roesler, Carolyn
Format: Article
Language:English
Subjects:
coherent reflection
CYGNSS
Global navigation satellite system
GNSS reflectometry
Land surface
Optical surface waves
Reflection
Rough surfaces
Spatial resolution
Spire
Surface roughness
surface water extent
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Summary:Coherent GNSS reflections over land predominantly occur over surface water bodies. This study presents a method to jointly use carrier phases and signal strengths of reflected signals to identify coherent reflections and applies it to the 50-Hz GNSS-R measurements from Spire Global Cubesats and CYGNSS microsatellites to map inland water bodies. A coherence detector was first developed using the circular statistics of carrier phase noises, identifying the input samples as coherent, semi-coherent, or incoherent. For any given track of data, we used this coherence detector to iteratively assess the coherency levels of the samples by a moving time window, then derived the coherency levels with the highest confidence. The circular statistics-based semi-coherent reflections with signal strengths above the prescribed threshold were regarded as coherent. The specular reflection points of the coherent reflections represent the locations of surface water. This method was applied to the Spire data to obtain the surface water extents for 1951 lakes and the CYGNSS data for 113 lakes. Compared to Global Surface Water Explorer observations, around 90% of the disagreements of the Spire data-based surface water boundaries are less than 0.73 km with a mean of 0.28 km and a standard deviation of 0.24 km. As for CYGNSS, ~90% of the disagreements are less than 0.43 km with a mean value of 0.18 km and a standard deviation of 0.16 km. The possible error sources are mainly fractional surface water, nearly flat and saturated ground surface, background land cover, and GNSS-R geometry.
ISSN:0196-2892
DOI:10.1109/TGRS.2022.3218254