Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Canopy height distributions were created from small-footprint airborne laser scanner data with an average sampling density of 1.13 points·m –2 collected over 132 sample plots and 61 forest stands. Field measurements of each plot were carried out within two concentric circles corresponding to fixed areas of 200 m 2 and 300 or 400 m 2 . The laser point clouds were thinned to approximately 0.25, 0.13, and 0.06 point·m –2 . For all comparisons, the maximum values of the first as well as last return canopy height distributions differed significantly between the full density and the thinned data. The combined effects of number of field plots, field plot sizes, and point densities on the accuracy of mean tree height, stand basal area, and stand volume predicted at stand level using a two-stage procedure combining field training data and laser data, were assessed using Monte Carlo simulation randomly selecting 75% and 50% of the field plots. The average standard deviation showed only a minor increase by decreasing point density and increased when the number of sample plots was reduced. The effects of field plot size varied with canopy structure and stem density.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it