Ground Validation of Seismic Line Forest Regeneration Assessments Based on Visual Interpretation of Satellite Imagery
Bibliographic record
Abstract
Seismic lines, which are narrow linear clearings used for hydrocarbon exploration, have accumulated throughout Alberta’s forest landscapes for decades. The inconsistent natural recovery of seismic lines over time has led to a fragmented landscape and has incited the need for restoration programs and associated monitoring of forest recovery on seismic lines. In this study, we evaluated a technique where we used satellite imagery to visually assign recovery classifications based on whether the seismic line remained >50% visible (Not Recovered), <50% visible (Fractionally Recovered), or not visible (Recovered) in upland mixedwood forests. We ground validated the recovery classification on 22 seismic lines using the recovery criteria of 2000 stems ha−1 and a mean tree height of 3 m. The categories of Recovered and Fractionally Recovered met the recovery criteria with 100% and 80% accuracy, respectively, while the Not Recovered category identified lines that failed to meet the recovery criteria with 83% accuracy. Based on these findings, visual interpretation of satellite imagery can be used to provide cursory-level recovery information for monitoring forest recovery on upland seismic lines at landscape-level scales.
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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 | 0.000 |
| 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) | 0.000 | 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 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".