Temporal analysis of forest structural condition at an acid mine site using multispectral digital camera imagery
Bibliographic record
Abstract
A large abandoned tailings deposit at a mine site near Timmins, Ontario, Canada has produced significant damage in an adjacent forest due to contamination and wind stress. Significant forest structure changes were measured between 1997 and 1999. A multivariate image-based forest structure index (FSI) was developed using canonical correlation analysis of 1997 field and airborne digital camera data. FSI included decreasing canopy closure and leaf area index, and increasing blown down and standing dead structure measures associated with image spectral, textural and radiometric fraction variables. An image model predicting FSI achieved an R 2=0.66. The model equation was then applied to 1999 airborne imagery to predict FSI for each plot. Comparing the 1999 image predicted FSI to that calculated from field data showed that the model was strong in predicting positive or no forest structure changes, but not increased structure degradation. The latter was due to the presence of herbaceous and shrub vegetation that had developed during the two-year period in open plots near the tailings where blow down was significant. The next research phase will derive means to separate these two signals in forests of open overstory.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".