Using a Canopy Reflectance Model for the Detection of Aspen Dieback from Multitemporal Landsat Thematic Mapper Data
Bibliographic record
Abstract
Trembling aspen (Populus tremuloides Michx.) is the predominant tree species in the aspen parkland and boreal transition ecoregions located within the Canadian Prairie provinces. Recent severe drought in this region has led to extensive dieback, mortality and reduced growth of trembling aspen trees but its precise spatial extent and occurrence is unknown. Tree level estimates of percent dieback were used to create an index of crown biomass loss at the plot level that could be related to the change values derived from satellite imagery. Multitemporal Landsat Thematic Mapper data representing pre-dieback (1999) and progressive stages of dieback conditions observed in 2001, 2003 and 2006 were analysed. Results suggest that image estimates of differences in crown closure derived from the inversion of the Li-Strahler canopy geometric-optical model were sensitive to canopy structure and the loss of crown biomass caused by dieback. Future work will focus on translating the loss in crown biomass to stand-level impact assessments on aspen forest productivity and biomass.
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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 | 0.001 |
| 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 | 0.001 |
| 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".