The effects of temporal decorrelation and topographic slope on forest height retrieval using airborne repeat-pass L-band polarimetric SAR interferometry
Bibliographic record
Abstract
We have explored the effects of temporal baseline and terrain slope on forest height estimation using L-band repeat-pass polarimetric synthetic aperture radar interferometry. Data were collected using NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar instrument over a study area exhibiting high slope topography in the Laurentides Wildlife Reserve of Québec, Canada. We used lidar-derived canopy height and terrain slope maps to quantify the decorrelation effects that distort the observed coherences compared to the random volume over ground forest model. We derived forest height maps for a number of different temporal baselines using both fixed model parameters and model parameters that varied with slope, and compared the results. Use of a look-up table for the terrain slope effects improved the estimated forest heights, but further work is necessary to see if slope corrections derived from lidar data for this study area can be applied to other study areas, or generalized to a theoretical model.
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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 | 0.002 |
| 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) | 0.000 | 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".