Evaluation of digital and film hemispherical photography and spherical densiometry for measuring forest light environments
Bibliographic record
Abstract
This study presents the results of a comparison of digital and film hemispherical photography as means of characterizing forest light environments and canopy openness. We also compared hemispherical photography to spherical densiometry. Our results showed that differences in digital image quality due to the loss of resolution that occurred when images were processed for computer analysis did not affect estimates of unweighted openness. Weighted openness and total site factor estimates were significantly higher in digital images compared with film photos. The differences between the two techniques might be a result of underexposure of the film images or differences in lens optical quality and field of view. We found densiometer measurements significantly increased in consistency with user practice and were correlated with total site factor and weighted-openness estimates derived from hemispherical photography. Digital photography was effective and more convenient and inexpensive than film cameras, but until the differences we observed are better explained, we recommend caution when comparisons are made between the two techniques. We also concluded that spherical densiometers effectively characterize forest light environments.
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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 | 0.003 | 0.008 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".