Advantages of satellite stereograms over monoscopic images from RADARSAT-1 for geological mapping and exploration
Bibliographic record
Abstract
Mapping rock units and associated geological structures can be difficult to elucidate from single SAR images. Through stereoscopic examination of suitable SAR stereopairs, however, it is often concluded that recognition and interpretation geological features is greatly improved. To provide guidelines for selecting appropriate image pairs, several RADARSAT-1 images from tropical and arctic environments covering a wide range of incidence angles were examined. Best results for geological interpretation were obtained from same-side stereopairs. Where terrain relief is high, sufficient vertical exaggeration is attained with relatively small intersection angles (5-10°), whereas low relief environments require larger angles of stereo intersection (>15°). The proportion of overlap between specific beam modes is latitude dependent, thus a judicious selection of image pairs is required based on both terrain characteristics and specifications of RADARSAT-1 orbital tracks and imaging modes.<br>Keyword: stereo
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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) | 0.001 | 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) | 0.003 | 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".