期刊
CANADIAN JOURNAL OF REMOTE SENSING
卷 46, 期 6, 页码 765-783出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/07038992.2020.1867974
关键词
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资金
- Canadian Space Agency (CSA) under the project Ecosystem Assessment and Monitoring (RCM Data Utilization & Application Plan (DUAP) IMOU) [14SURCM007]
We investigated the potential of using Synthetic Aperture Radar (SAR) imagery from three different frequencies: X-, C-, and L-band, to characterize coastal wetlands in the Great Lakes. Three sets of SAR data acquired over the Bay of Quinte, Ontario, Canada between 2016 and 2018 from Radarsat-2, 2016 from TerraSAR-X, and 2018 from ALOS-2 satellites were processed using small baseline subset (SBAS) Interferometric SAR (InSAR) techniques to provide maps of surface changes in marshes and swamps. Results showed that SAR backscatter and coherence were sensitive to sensor characteristics (frequency, polarization, incidence angle, acquisition interval), changes in water level, and phenology. InSAR time series observations were evaluated using measurements from water level loggers based on correlation and root mean square error (RMSE) from a linear regression model. Correlation between InSAR measurements and water level changes in the field varied from -1 to 1 depending on the site, type of wetland vegetation, and incidence angle. Although results from some sensor modes provided good correlation (0.77-1) at a few locations, the low fringe rate and large RMSE between 4 and 64 cm indicated that InSAR observations of water level changes in the dynamic wetland environment were generally underestimated.
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