Dual-Polarimetric C- and X-Band SAR Data for Coastline Extraction
Why this work is in the frame
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Bibliographic record
Abstract
This study proposes a new metric to process dual-polarimetric coherent and incoherent synthetic aperture radar (SAR) data for coastline extraction purposes. The metric, based on the correlation between co- and cross-polarized channels, allows discriminating land from sea in an unsupervised way. Then, simple image processing is adopted to extract continuous coastline from the binary image. Experiments, undertaken on multipolarization C- (RadarSAT-2 and Sentinel-1) and X-band (Cosmo-SkyMed) SAR data collected in South of Italy together with Global Positioning System ground truth, confirm the soundness of the method which is shown to be both effective (a whole SAR scene is processed in seconds) and accurate (the mean error is less than $5$ and $7$ pixels for RadarSAT-2 and CosmoSkyMed, respectively).
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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 it