Wetland Monitoring Using SAR Data: A Meta-Analysis and Comprehensive Review

Abstract

<jats:p>Despite providing vital ecosystem services, wetlands are increasingly threatened across the globe by both anthropogenic activities and natural processes. Synthetic aperture radar (SAR) has emerged as a promising tool for rapid and accurate monitoring of wetland extent and type. By acquiring information on the roughness and moisture content of the surface, SAR offers unique potential for wetland monitoring. However, there are still challenges in applying SAR for mapping complex wetland environments. The backscattering similarity of different wetland classes is one of the challenges. Choosing the appropriate SAR specifications (incidence angle, frequency and polarization), based on the wetland type, is also a subject of debate and should be investigated more thoroughly. The geometric distortion of SAR imagery and loss of coherency are other remaining challenges in applying SAR and its processing techniques for wetland studies. Hence, this study provides a systematic meta-analysis based on compilation and analysis of indexed research studies that used SAR for wetland monitoring. This meta-analysis reviewed 172 papers and documented an upward trend in usage of SAR data, increasing usage of multi-sensor data, increasing integration of C- and L- bands over other configurations and higher classification accuracy with multi-frequency and multi-polarized SAR data. The highest number of wetland research studies using SAR data came from the USA, Canada and China. This meta-analysis highlighted the current challenges and solutions for wetland monitoring using SAR sensors.</jats:p>

Multi-Source EO for Dynamic Wetland Mapping and Monitoring in the Great Lakes Basin

“…Simulated RCM data was also able to adequately assess short term temporal changes within wetlands. The addition of L-band data will likely increase classification accuracy, as multi-frequency SAR has been shown to have good results for wetland classification in the Great Lakes [85], and multi-frequency classifications have slightly higher overall accuracies compared to singlefrequency classifications [86]. Therefore, the potential of combined RCM and NISAR data could prove to be unparalleled for dynamic wetland monitoring.…”

Using InSAR to identify hydrological connectivity and barriers in a highly fragmented wetland

“…Its existence could not have otherwise been confirmed from optimal imagery or fieldwork. The management measures required to improve water circulation and connectivity vary depending on the wetland and the specific environmental problems generated by the undesired level of hydrological connectivity (See as examples Adeli et al, 2020; Feagin, Johns, Huff, Abdullah, & Fritz‐Grammond, 2020; Lee, Yuan, & Jung, 2020; Siles, Trudel, Peters, & Leconte, 2020; Wemple et al, 2017). Dredging can be used to remove sediments or installing culvert pipes across the ditch may help to improve the connectivity of this area.…”

Monitoring Dynamic Evolution of the Glacial Lakes by Using Time Series of Sentinel-1A SAR Images

“…Synthetic aperture radar (SAR) represents an alternative to optical satellites for feature classification [22,23] and change detection [24,25] with the capability to collect data under all weather conditions without the restriction of clouds [26]. Since the smooth water surface will cause the incident SAR signal to be specularly reflected, the backscattered intensity in the SAR image corresponding to the water bodies is generally lower than their surroundings.…”