Investigations of GNSS-R for Ocean Wind, Sea Surface Height, and Land Surface Remote Sensin

While various techniques including satellite remote sensing have been used to monitor Earth's surface and atmosphere, the increasing recent interest in the use of Global Navigation Satellite Signal Reflectometry (GNSS-R), which uses reflected GNSS signals from the Earth's surface for remote sensing applications, motivates studies of GNSS-R for retrieving geophysical parameters including sea surface height, wind speed and direction, and land surface properties. This method provides exceptional global coverage and shorter revisit times compared to conventional satellite missions. Also, it is stable, accurate, and cost effective. This dissertation examines how GNSS-R datasets can be exploited for retrievals of sea surface height (SSH) (including consideration of the electromagnetic (EM) bias error source,) wind direction, sea ice coverage, and land surface properties. Because the CYGNSS (Cyclone Global Navigation Satellite System) constellation provides extensive coverage in time and space, studies of the temporal behaviors of oceanic winds are also reported.;A "Full DDM" (Delay-Doppler Map) retrieval method is introduced for sea surface height retrievals. Various conditions for retrieval simulations are demonstrated, including fixed geometry, varying geometries with a nature run wind field dataset, and TDS-1 (TechDemosat-1) satellite measurements. The utility of additional spatial and temporal averaging to further beat down retrieval errors is also discussed. Also, the electromagnetic (EM) bias, which is one of error sources in ocean altimetry due to the asymmetric properties of sea waves, is studied for GNSS-R. It is shown that the EM bias varies approximately as the cosine of the specular angle, and the contributions of sea waves on the order of the electromagnetic wavelength or larger are also illustrated through the Monte Carlo simulations performed. Furthermore, the dissertation investigates the influence of wind direction on both purely specular bistatic scattering geometries and on near specular geometries that contribute to the DDMA (DDM Average) quantity used in GNSS-R sea surface wind speed remote sensing.;The temporally "clumped" properties of CYGNSS measurements are also examined. Examples with simulations and CYGNSS measurements are provided to indicate the potential of changes within a clump to produce a "rapid revisit" product for detecting convective activity. Detector results from this analysis are compared with cyclone and front boundary information. Finally, observations of the TDS-1 and CYGNSS missions over land surfaces are examined with land surface forward models including their coherent and incoherent components. A correlation method is examined and verified in detecting sea ice and coherent returns.