Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar
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Bibliographic record
Abstract
This study examines the distribution of laser pulse returns obtained from coincident airborne and terrestrial lidar surveys of a closed-canopy red pine (Pinus resinosa) plantation. The purpose of this study is to improve our understanding of laser pulse sampling within closed canopies so that estimates of forest structural variables (e.g., biomass, needle-leaf area, and base-of-live-crown) can be improved at the individual tree and stand levels using lidar. The results of this study indicate the following: (1) There is a statistically significant difference between field measurements of tree height and estimates derived from the maximum laser pulse return from airborne and terrestrial lidar. In both cases, maximum laser pulse returns underestimate tree height by 1 m, on average. (2) Both terrestrial and airborne lidar are unable to discern the base of the measured live crown. Laser pulse returns from airborne lidar are biased towards the top of the tree crown, i.e., lowest laser pulse returns occur 1.4 m on average higher in the canopy than the measured base-of-live-crown. On the other hand, terrestrial lidar captures dieback at the base of the live crown, thereby lowering the base-of-live-crown estimate by 6.6 m, on average. (3) Median airborne laser pulse returns within the canopy (20.4 m), believed to be associated with needle leaf area, occur below the maximum frequency of laser pulse returns (20.8 m) but higher in the canopy than the height of maximum crown diameter obtained from terrestrial lidar (18.0 m). The bias of airborne laser pulse reflections towards the top of the canopy with less penetration to a depth where the maximum crown diameter occurs may result in an underestimation of the needle leaf area. The results of this research suggest that future research should focus on improving our understanding of how laser pulse returns are "triggered" within vegetated environments and how canopy properties or data acquisition parameters may influence the location of this "trigger" event.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it