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RSS FeedsRemote Sensing, Vol. 10, Pages 1749: Impact of the Elevation Angle on CYGNSS GNSS-R Bistatic Reflectivity as a Function of Effective Surface Roughness Over Land Surfaces (Remote Sensing)

 
 

8 november 2018 12:00:33

 
Remote Sensing, Vol. 10, Pages 1749: Impact of the Elevation Angle on CYGNSS GNSS-R Bistatic Reflectivity as a Function of Effective Surface Roughness Over Land Surfaces (Remote Sensing)
 


The Earth`s surface bistatic reflectivity is experimentally characterized using the novel Global Navigation Satellite Systems Reflectometry (GNSS-R) L-band passive multistatic radar technique from the Cyclone Global Navigation Satellite Systems (CyGNSS) eight-microsatellite constellation. The focus of this study is to evaluate the influence of the GNSS satellites` elevation angle on , as a function of soil moisture content (SMC) and effective surface roughness parameter . As the average response, the change of the scattering regime at a global scale and considering also vegetated surfaces appears at ? ? 55°. This empirical observation is understood as a change on the dominant scattering term, from incoherent to coherent. Then, the correlation of ?LHCP,CyGNSS and SMC is evaluated as a function of ?e over specific sparsely vegetated target areas. The smoother the surface, the higher the angular variability of the Pearson correlation coefficients. Over croplands (e.g., Argentinian Pampas), an improved correlation coefficient is achieved over angular ranges where the coherent scattering regime becomes the dominant one. As such, this function depends on the surface roughness. The maximum correlation coefficients are found at different ? for increasing mean roughness levels: rPampas ? ? 0.78 at ? ? [60,70]°, rIndia ? 0.72 at ? ? [50,60]°, and rSudan ? 0.74 at ? ? [30,40]°. SMC retrieval algorithms based on GNSS-R multi-angular information could benefit from these findings, so as to improve the accuracy using single-polarized signals.


 
140 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 10, Pages 1750: Estimating Changes in Leaf Area, Leaf Area Density, and Vertical Leaf Area Profile for Mango, Avocado, and Macadamia Tree Crowns Using Terrestrial Laser Scanning (Remote Sensing)
Remote Sensing, Vol. 10, Pages 1748: Generation of High Resolution Vegetation Productivity from a Downscaling Method (Remote Sensing)
 
 
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