The application of digital photogrammetry and image analysis techniques to derive tree and stand characteristics
Bibliographic record
Abstract
Ground-based forest inventory surveys can provide highly accurate measurements of tree and stand characteristics, but these are expensive to carry out. Aerial photography has been used for several decades as a tool in forest management and inventory. However, conventional methods of interpretation are both time-consuming and costly, with results varying among interpreters. With continuing development of personal computer technology, aerial photographs have become more accessible for digital analysis. This paper presents the potential operational use of digitized aerial photographs for the estimation of tree and stand characteristics of two forest plantations of Sitka spruce (Picea sitchensis (Bong.) Carrière) in Scotland. The digitized aerial photographs were processed using softcopy photogrammetry, and image analysis techniques were used for individual tree crown delineation. For the first site the estimations of stand top height, basal area, volume, biomass, and density (23.7%) were similar to the ground-measured stand characteristics (±10%), whereas for the second site the estimations were less accurate mainly because of the nonoptimal illumination conditions during the acquisition of the aerial photographs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 teacher head, 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".