Capability of Radarsat-1 for estimation of ocean surface current on the Scotian Shelf
Bibliographic record
Abstract
Doppler shifts in space-based synthetic aperture radar (SAR) data are due to movement of objects in the image area. These frequency shifts are most obvious in fast moving point targets such as ships. However, an area target such as the sea surface can also cause a measurable Doppler shift from which ocean surface currents can be estimated. We compare surface currents derived from three standard mode Radarsat-1 scenes over the Scotian Shelf to in situ currents measured with 21 self-locating datum marker buoys (SLDMBs). The SLDMBs drift with the local surface current, and their locations, obtained every 30 minutes via Argos satellite, are used to calculate the current. Three Radarsat-1 scenes were processed by Atlantis Scientific of Ottawa, Canada, to obtain the component of the surface current vector perpendicular to the path of the satellite. The results show that the noise in the derived Doppler shift was comparable to the Doppler shift expected from the relatively low surface currents prevalent on the Scotian Shelf. While it was concluded that present space-based SAR technology cannot provide accurate surface current data for Scotian Shelf conditions, the methodology and results provide a useful metric by which future SAR systems can be evaluated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".