Climate and Environmental Monitoring using GNSS Remote Sensing

Abstract

The potential of Global Navigation Satellite System (GNSS) signals for remote sensing applications has been widely recognized. The widespread availability of GNSS signals, whether in direct form or as reflections, enables the extraction of various Earth system component parameters. This thesis comprises of multiple investigations conceming the evaluation and improvement of data products derived from GNSS remote sensing, as well as the exploration of other potential applications.

Exemplary datasets from two classes of GNSS data products are used. The thesis presents studies based on reflected signals of Medium Earth Orbiting (MEO) GNSS satellites in bistatic radar configuration. The reflected signals can be received by ground-based receivers or spacebome receivers onboard Low Earth Orbiting (LEOs) satellites. In this sense, the thesis focuses on a new generation of observations from the spacebome GNSS-R technique for flood detection purposes. Finally, ground-based GNSS-Reflectometry (GNSS-R) measurements with demonstrated applications for environmental monitoring.

The initial research in this thesis centers on a dataset derived from advanced spaceborne GNSS-R observations, specifically addressing flood detection and mapping during intense rainfall events. Flood detection and produced maps play essential roles in policymaking, planning, and implementing flood management options. The investigation is carried out in a region prone to flooding, necessitating continuous monitoring with timely observations. A threshold of about 11 dB or more could be distinguished between the inundated and noninundated areas in the regions of interest. The flood-affected areas were mapped on Google Maps. The area of the flooded regions was estimated to be about 19,644 km2 or 10.8% of the study area. The findings underscore the capability of spacebome GNSS­R to deliver observations characterized by the necessary sensitivity and frequent revisits, enabling the identification and mapping of inundated regions.

A GNSS-R dataset from a coastal experiment has been used in three studies of this thesis to investigate possible quality improvements of sea surface characterization measurements. The dataset includes polarimetric observations recorded using a dedicated reflectometry receiver with multiple input antennas. The antennas have Right- and Left-Handed Circular Polarizations (RHCP and LHCP) and are installed at zenith and sea-looking orientations. The studies show that polarimetric observations can significantly improve the quality of the GNSS-R measurements. The dataset is used to assess GNSS-R sea-level monitoring under different scenarios. The effects of sea surface roughness, wind effect, polarization and orientation of the antenna, and the frequency of the GNSS signal are studied. The results show that the roughness and wind can degrade the accuracy of the GNSS-R sea-level measurements. The best GNSS-R altimetric performance is observed when combined multi-frequency measurements are used from a sealooking antenna with an LHCP design. The RMSEs between GNSS-R sea surface heights for LHCP sea-looking antenna with respect to collocated tide gauge (TG) measurements are 2.4, 3.0, 4.5, and 5.6 cm for 6-, 3-, 1-, and 0.25-h window sizes, respectively. The seaward orientation can improve the accuracy of RHCP sea level results up to 20%, 13%, and 25%, respectively, for L1, L2, and L12. This improvement can reach about 48%, 50%, and 47% for L1, L2, and L12 if the tilted antenna is LHCP. The data set with this type but longer is also applied for tidal analysis. The detection results highlight a good match between GNSS-R and TG. we estimate the amplitude and phase of standard tidal harmonics from the two datasets. The results show an overall good agreement between the datasets with a few exceptions. There are some differences between the estimated amplitude (K1) and phase (K1,OO1,K2,and MK3) values. The GPS orbital period can be one of the main contributors to the observed differences as reported by previous studies. This effect is more noticeable in the phase of the tidal harmonics. Higher harmonics, i.e., the periods shorter than 3 hours show stronger signatures in GNSS-R data.