The RADARSAT Constellation Mission Core Applications: First Results

Remote Sensing

Fariba Mohammadimanesh¹  Brian Brisco²  Ian Olthof²  Saeid Homayouni³  Masoud Mahdianpari⁴  Mohammed Dabboor⁵  Mohammed Shokr⁶ 

[1] C-CORE, 1 Morrissey Road, St. John’s, NL A1B 3X5, Canada;Canada Centre for Mapping and Earth Observation, Natural Resources Canada, Ottawa, ON K1S 5K2, Canada;Centre Eau Terre Environnement, Institut National de la Recherche Scientifique (INRS), Quebec City, QC G1K 9A9, Canada;Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada;Science and Technology Branch, Environment and Climate Change Canada, Dorval, QC H9P 1J3, Canada;Science and Technology Branch, Environment and Climate Change Canada, Downsview, ON M3H 5T4, Canada;

关键词: SAR;    RCM;    compact polarimetry;    flood;    sea ice;    wetland;   

DOI  :  10.3390/rs14020301

来源: DOAJ

【 摘 要 】

The Canadian RADARSAT Constellation Mission (RCM) has passed its early operation phase with the performance evaluation being currently active. This evaluation aims to confirm that the innovative design of the mission’s synthetic aperture radar (SAR) meets the expectations of intended users. In this study, we provide an overview of initial results obtained for three high-priority applications; flood mapping, sea ice analysis, and wetland classification. In our study, the focus is on results obtained using not only linear polarization, but also the adopted Compact Polarimetric (CP) architecture in RCM. Our study shows a promising level of agreement between RCM and RADARSAT-2 performance in flood mapping using dual-polarized HH-HV SAR data over Red River, Manitoba, suggesting smooth continuity between the two satellite missions for operational flood mapping. Visual analysis of coincident RCM CP and RADARSAT-2 dual-polarized HH-HV SAR imagery over the Resolute Passage, Canadian Central Arctic, highlighted an improved contrast between sea ice classes in dry ice winter conditions. A statistical analysis using selected sea ice samples confirmed the increased contrast between thin and both rough and deformed ice in CP SAR. This finding is expected to enhance Canadian Ice Service’s (CIS) operational visual analysis of sea ice in RCM SAR imagery for ice chart production. Object-oriented classification of a wetland area in Newfoundland and Labrador by fusion of RCM dual-polarized VV-VH data and Sentinel-2 optical imagery revealed promising classification results, with an overall accuracy of 91.1% and a kappa coefficient of 0.87. Marsh presented the highest user’s and producer’s accuracies (87.77% and 82.08%, respectively) compared to fog, fen, and swamp.

【 授权许可】

Unknown