Characterization of the Terra Nova Bay Polynya Using Dual-Polarimetric C-Band SAR Measurements
Bibliographic record
Abstract
In polar regions, coastal polynyas are key drivers for climate since they represent the primary source of ice mass production and oceanic circulation. In this study, multipolarization C-band synthetic aperture radar (SAR) measurements acquired by the Radarsat-2 satellite mission are exploited to observe the Terra Nova Bay (TNB) coastal polynya in the Ross Sea, Antarctica. Incoherent and coherent features, extracted from dual-polarimetric SAR measurements, are used to characterize the TNB coastal polynya under different environmental conditions. The analysis is also supported, when available, by independent optical remote sensing information collected by the thermal infrared channels of the moderate resolution imaging spectroradiometer and by ancillary on-site information about wind and air temperature collected by automatic weather stations. Experimental results show that the SAR plays a key role in providing information about the TNB polynya thanks to its fine spatial resolution and its almost continuous imaging capabilities. In addition, dual-polarimetric SAR offers unprecedented opportunities with respect to single-polarization SAR in performing accurate and unsupervised classification of the area within the polynya. Hence, a more accurate estimation of the polynya extent and the fractional area coverage of sea water within the polynyas obtained.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".