Multi-Polarisation C-Band SAR Imagery to Estimate the Recent Dynamics of the d’Iberville Glacier
Bibliographic record
Abstract
To monitor polar regions is of paramount importance for climatological studies. Climate change due to anthropogenic activities is inducing global warming that, for example, has resulted in glacier melting. This has had a significant impact on sea levels and ocean circulation. In this study, the temporal trend of the marine-terminated d’Iberville glacier (Ellesmere Island, Canada) is analysed using C-band synthetic aperture radar satellite imagery collected by the Radarsat-2 and Sentinel-1 missions. The data set consists of a time series of 10 synthetic aperture radar data collected from 2010 to 2022 in dual-polarimetric imaging mode, where a horizontally polarised electromagnetic wave was transmitted. An automatic approach based on a global threshold constant false alarm rate method is applied to the single- and dual-polarisation features, namely the HH-polarised normalised radar cross-section and a combination of the HH- and HV-polarised scattering amplitudes, with the aim of extracting the ice front of the glacier and, therefore, estimating its behaviour over time. Independent collocated satellite optical imagery from the Sentinel-2 multi-spectral instrument is also considered, where available, to support the experimental outcomes. The experimental results show that (1) the HH-polarised normalised radar cross-section achieved better performance with respect to the dual-polarised feature, especially under the most challenging case of a sea-ice infested sea surface; (2) when the HH-polarised normalised radar cross-section was considered, the ice front extraction methodology provided a satisfactory accuracy, i.e., a root mean square error spanning from about 1.1 pixels to 3.4 pixels, depending on the sea-surface conditions; and (3) the d’Iberville glacier exhibited, during the study period, a significant retreat whose average surface velocity was 160 m per year, resulting in a net ice area loss of 2.2 km2 (0.18 km2 per year). These outcomes demonstrate that the d’Iberville glacier is behaving as most of the marine-terminated glaciers in the study area while experiencing a larger ice loss.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".