Ice Cover Delineation Over Devon Iceland Using Sentinel Polarimetric SAR and Optical Data
Accurate information on the extent and dynamics of ice cover is important on a global scale. Owing to the daynight and weather-independent imagery capabilities, Sentinel-1 (S1) is a reliable source for ice monitoring using synthetic aperture radar (SAR) images. Therefore, this study focuses on an un...
| Main Authors: | , , |
|---|---|
| Format: | Conference Object |
| Language: | English |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://zenodo.org/record/8246262 https://doi.org/10.5281/zenodo.8246262 |
| Summary: | Accurate information on the extent and dynamics of ice cover is important on a global scale. Owing to the daynight and weather-independent imagery capabilities, Sentinel-1 (S1) is a reliable source for ice monitoring using synthetic aperture radar (SAR) images. Therefore, this study focuses on an unsupervised method for extracting ice cover by exploiting dual-pol S1 SAR data over Devon Island, which is surrounded by sea. We adopted a constant false alarm rate (CFAR) detector for ice cover detection by examining the empirical distribution of a given metric over a ice region, followed by statistical comparison of the resulting distribution with the theoretical “Burr” distribution to derive the CFAR threshold value. To achieve ice detection, a binary image is first retrieved, and then the ice edges are quantified using the Canny edge detector. To evaluate the effectiveness of the proposed method, we applied it to SAR data from a challenging environment, including terrain, ice, and water. The results were further verified using Sentinel-2 (S2) as the ground truth data, which showed the maximum correlation in the extraction. Our findings demonstrate the validity of the proposed method for ice cover extraction using Sentinel-1 data. |
|---|