3-D Radargrammetric Modeling of RADARSAT-2 Ultrafine Mode: Preliminary Results of the Geometric Calibration
Bibliographic record
Abstract
The geometry and the accuracy of the 3-D cartographic localization of RADARSAT-2 images are being evaluated as part of the Canadian Space Agency's Science and Operational Applications Research program. In a first step, the Toutin's 3-D physical model, previously developed for RADARSAT-1, was adapted to RADARSAT-2 sensor and applied to two ultrafine mode images (U2 and U25) acquired over an area in Beauport, Quebec. Both the 3-D modeling computed with only 12 ground control points and its geometric localization were evaluated with different check data: 1) independent check points; 2) the two quasi-epipolar images; 3) the two orthoimages; and 4) 1-m accurate orthophotos. All four results and validations are in agreement and confirm that the 3-D geometric localization and restitution accuracy are 1 m in planimetry and 2 m in elevation. The checked data error being included in these evaluations and the relative error computed from the quasi-epipolar comparison provided a high level of confidence that the precision of Toutin's 3-D radargrammetric model is better than 0.25 m.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".