Peatland ecosystems exhibit a wide range of biophysical conditions and Synthetic Aperture Radar (SAR) remote sensing provides a method to collect information about these conditions across large areas. The overarching purpose of this thesis was to advance understanding of SAR backscatter response to peatland hydrology and develop new approaches for remote mapping and monitoring of peatland environments with SAR. Specifically, this thesis aimed to 1) improve methods for peatland ecosystem mapping and classification accuracy assessment with a Random Forest classifier; and 2) develop methods for surface soil moisture and water table depth retrieval in peatlands using SAR remote sensing data. At Alfred Bog, a peatland in eastern Ontario, Canada, a Random Forest classification workflow was developed and enabled the creation of a site-wide peatland ecosystem map, which was used to better understand the SAR response to hydrological and vegetation conditions. For the retrieval of surface hydrologic information, SAR data were compared with trends in soil moisture, water table and vegetation spatial variability and change over time. Various polarimetric parameters were used to build statistical models of soil moisture and, in some cases, resulted in high explained variance but independent validation indicated that models were over-fit. These results are important, as many examples were found in the literature where, through statistical models, SAR was reported to be a strong predictor of soil moisture but models were not validated. To determine if models could predict soil moisture from SAR at times when no field measured data existed, linear mixed-effects models were built. These accounted for the temporal autocorrelation due to the repeated measures design of field data. While some models resulted in high explained variance, most of the explained variance was attributed to the variability between peatland classes and/or the specific date that the image was acquired, rather than the SAR data itself. Overall, this thesis points to some fundamental limitations on our ability to accurately monitor peatland hydrology with SAR due to the complexity of the scattering response. It highlights a need for extensive field monitoring campaigns and testing to further refine approaches for remote hydrologic monitoring in natural environments.