Use of remote sensing in reclamation assessment at Teck Cominco’s Bullmoose mine site
Bibliographic record
Abstract
The Bullmoose mine site is located in northeastern British Columbia, 40 km west of the town of Tumbler Ridge. The mine was an open-pit operation that produced metallurgical coal from October 1983 until its closure in April, 2003. The mine development footprint covers 789 hectares, and includes the Engelmann Spruce – Subalpine Fir moist very cold Bullmoose variant (ESSFmv2), the subalpine ESSFmvp2 parkland, and Alpine Tundra biogeoclimatic classes (ranging in elevation from the plant site, at 1100 m a.s.l. in the Bullmoose Creek valley, to waste dumps located at 1800 m). As a component of assessing reclamation to date and to prepare for closure, Bullmoose Operating Corporation and C.E. Jones & Associates Ltd. undertook in 2002 and 2003 a site-wide assessment on the status and success of currently reclaimed areas on the mine site. To accomplish this, a reclamation assessment program was developed using supervised computer classification of satellite imagery to identify discrete vegetation units on the reclaimed mine site. Ground-truthing using established reclamation success-and-sustainability assessment methods was conducted in August 2002 to validate and refine the classification system. The remote sensing-based classification resulted in the definition of 10 vegetation classes on reclaimed coal waste on the Bullmoose mine site. The defined classes are identifiable by unique spectral signatures, and are statistically separable based on selected ground-truth vegetation productivity and sustainability parameters. This information will be used to document achievement of post-closure equivalent productivity objectives on older reclaimed sites, and to predict the success of more recent reclamation, while reducing the need for more costly and labour-intensive ground-based assessment work. This paper summarizes the methods employed and results derived from this remote sensing-based assessment program.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".