MODELO DIGITAL DE SUPERFICIE A PARTIR DE IMÁGENES DE SATÉLITE IKONOS PARA EL ANÁLISIS DE ÁREAS DE INUNDACIÓN EN SANTA MARTA, COLOMBIA*
Bibliographic record
Abstract
Ikonos is one of the available high-resolution imagery earth observation satellites, with the ability to capture at once stereoscopic images of the same area allowing the extraction of Digital Surface Models (DSM). This paper describes the extraction process of a DSM Ikonos image of the Santa Marta city coastal area obtained images from a National Bank of the Geographic Institute Agustin Codazzi. In the topography generation process, from the sensor and orbit parameters of the image, the Rational Polynomial Coefficients values were simulated and the three-dimensional terrain model was achieved throughout the application of the algorithm proposed by Thierry Toutin from the Canadian Institute of Remote Sensing. The DSM and the obtained products were important inputs for the analysis of possible flood areas. Even though the accuracy of the model cannot directly trace a sub-metric flood line, the described procedure can be seen as a low cost and rapid preliminary analysis of risk areas, relevant for management and planning.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".