The use of aerial photographs to distinguish between stocking and density of western hemlock stands on the University of British Columbia Research Forest, Haney, B.C.
Bibliographic record
Abstract
Quantitative measures of stand density and stocking are very important because only with full knowledge of the growing stock can a forest be managed efficiently. Stocking is concerned with fraction of area occupied with trees. Density is related to the degree of crowding within the area occupied. These quantitative values are determined by parameters that could be measured on the ground and on aerial photographs. The methods used to estimate height, crown width, and crown closure from aerial photographs are thoroughly described. The writer also describes the stocking and density conditions under which trees grow, with illustrations by both theoretical models and actual sample plot crown models. Forty-seven sets of ground and photo-measurements were taken and analysed by simple and multiple regression methods. A comparison of photo and ground values was then made to evaluate the usefulness of aerial photographs for density and stocking measurements. The correlation of the ratio of height (Ht) to crown width (CW) from the ground and photo data to age, site index, crown closure, basal area, adjusted basal area, crowding factor and adjusted crowding factor were also studied. Eight assumptions regarding normality of density and full stocking were made so that the interrelationship between the individual density and stocking measurements could be studied more effectively. It is concluded that Ht/CW ratios are measurable from aerial photographs and shown that they are useful as a measure of stand density and stocking.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".