Abstract
In this study, synthetic aperture radar (SAR) data from TerraSAR-X were compared with RADARSAT-2 data to evaluate their effectiveness for river ice monitoring on the Peace River. For several years RADARSAT-2 data have been successfully used for river ice observation. However, it is important to take into account data from other satellites as they may provide solutions when it is not possible to obtain images from the preferred system (e.g., in the case of acquisition priority conflicts). In this study we compared three TerraSAR-X (X-band) and three RADARSAT-2 (C-band) datasets acquired in December 2013 on a section of the Peace River, Canada. For selected classes (open water, skim ice, juxtaposed skim ice, agglomerated skim ice, frazil run and consolidated ice) we compared backscattering values in HH and VV polarisation and performed Wishart supervised classification. Covariance matrices that were previously filtered using a refined Lee filter were used as input data for classification. For all data sets the overall accuracy was higher than 80%. Similar errors associated with classification output were observed for data from both satellite systems.
Highlights
River ice is known to affect many of the world’s largest rivers
The lowest backscattering values are associated with open water (OW) and vary from -30 dB to -20 dB depending on the incidence angle and frequency
The aim of this study was to compare TerraSAR-X data with RADARSAT-2 data to evaluate their usefulness for river ice monitoring on the Peace River
Summary
River ice is known to affect many of the world’s largest rivers. 60% of rivers in the Northern Hemisphere experience its significant seasonal effect (Prowse, 2005). The main hydrological consequence of river ice is its influence on river discharge. Ice-induced extreme flow events can result in serious economic issues such as floods or damages to water power plant infrastructure. Satellite data have vast potential for river ice monitoring because they span large areas. Synthetic Aperture Radar (SAR) systems are promising, they can acquire data during the day or night without regard to cloud cover. Application of earth observation data for river ice monitoring has been discussed since at least the 1980s (Hall, 1985)
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