KEY WORDS GEOMETRIC PROCESSING OF IKONOS GEO IMAGES WITH DEM
Bibliographic record
Abstract
Thirteen Pan or XS IKONOS Geo-product images over seven study sites with various environments and terrain were tested using different cartographic data and accuracies using a parametric modelling developed at the Canada Centre for Remote Sensing. The objectives were to track the error propagation during the full geometric correction process (bundle adjustment and ortho-rectification). When ground control points (GCPs) are less than 3-m accurate, 20 GCPs over the full image is a good compromise to obtain 3-4 m accuracy in the bundle adjustment. When cartographic co-ordinates are better than 1-m, 10 GCPs are then enough to increase to 2-3 m accuracy with either panchromatic or multiband images. The remaining error is due to GCP definition and plotting. Quantitative and qualitative evaluations of ortho-images were performed with independent check points or digital vector files. Positioning accuracy of 2-4 m is achieved for the ortho-images depending of the elevation accuracy (DEM and grid spacing). To achieve a better final positioning accuracy, such as 1 m, 1-2 m accurate DEM with fine grid spacing is required in addition to well-defined GCPs benchmarked on the ground. 1.
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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 | 0.001 |
| 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 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".