Auteur : Kim, D.

Co-Auteur : Lee, H., Laraque, A., Tshimanga, R.M., Yuan, T., Jung, H.C., Beighley, E., Chang, C.

Review : International Journal of Remote Sensing

Lien : https://www.sciencedirect.com/science/article/pii/S0341816219300803

Abstract

Previous studies using synthetic aperture radar (SAR) backscattering coefficients have been used to distinguish vegetation types, to monitor flood conditions, and to assess soil moisture variations over the wetlands. Here, we attempted to estimate spatio-temporal water level variations over the central Congo mainstem covered with aquatic plants using the backscattering coefficients from the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) Scanning SAR (ScanSAR) images and water levels from Envisat altimetry data. First, permanent open water, forest, macrophytes, and herbaceous plants have been classified over the central Congo Basin based on statistics of the backscattering coefficient values. Second, we generated multi-temporal water level maps over part of the Congo mainstem based on the relationship between Envisat altimetry-derived river-level changes and PALSAR ScanSAR backscattering coefficient variations. Finally, the water level maps were validated with Ice, Cloud and land Elevation Satellite (ICESat) altimetry-derived water levels. We obtained overall root mean square difference (RMSD) of 67.27 cm at 100-m scale resolution of PALSAR ScanSAR. Our study shows that we can obtain reasonable estimates of water levels of the rivers covered with seasonally floating or emergent macrophytes from backscattering coefficients. Furthermore, it is expected that the generated water level maps can be used as a ‘true’ data set to perform pre-launch study of the Surface Water Ocean Topography (SWOT) mission to be launched in 2021.