ESTIMATING INDIVIDUAL TREE HEIGHTS AND DBHS FROM VERTICALLY DISPLACED SPHERICAL IMAGE PAIRS
Bibliographic record
Abstract
Individual tree parameters, such as diameter at breast height (DBH) and tree height, are fundamental measurements in forest inventory, and often labour intensive and require significant financial expenditures. Applying digital imaging in forest inventory is an efficient way to decrease the workload. In this study, spherical images taken using a novel commercial 360° camera (Ricoh Theta S) and stereographic geometry were applied to obtain these parameters directly without stitching multiple images from common cameras. This technology was validated in both a sparse urban forest (pairwise comparison) and denser real forest (distributional comparison) in Atlantic Canada. The DBH (r2 > 0.76) and height (Dmax < 0.25, K-S test) showed high correspondence with field measures. The spherical camera represents a low-cost option to terrestrial laser scanning and has potential to produce more accurate forest-level estimates with quicker field and office processing time than current under-canopy remote sensing technologies.
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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) | 0.001 | 0.001 |
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".