LIDAR Derived Forest Metrics - Calvert Island - British Columbia - Canada
Bibliographic record
Abstract
72 LIDAR Derived Forest Metrics - Calvert Island - 20 Meter Spatial Resolution LIDAR forest metrics have been developed for the Calvert Island region. The data are in 20 meter resolution and detail a number of variables about the vegetation layer above the bare earth model. Forest metrics have been grouped to show major statistical themes such as gap fraction, stem height, and density. The information is valuable for classifying forest structure and better understanding ecosystem dynamics. LIDAR Forest Metrics Produced by GWF LiDAR Analytics A full list of derived forest metrics produced by G.W. Frazer is listed at the end of this abstract. LIDAR flights conducted in 2012 and 2014 covered all of Calvert and Hecate Island. Flights were completed in August of 2012 (Terra Remote Sensing) and August of 2014 (Brian Menounos UNBC). Area-based canopy height and density metrics are derived directly from a height-normalized LAS point cloud using proprietary software developed by G.W. Frazer (note: Fusion and LASTools are respectively open-source and commercial software that can be used to extract various area-based canopy metrics). These gridded products (approximately 55 bands) have a user-defined 20 m spatial resolution and include (i) height-based statistics (e.g., min., max., mean, moments, percentiles), (ii) density-based statistics (i.e., gap fraction, canopy cover at fractional and absolute heights above the ground surface), and (iii) diagnostic information (e.g., number of laser points in each cell, number of laser points classified as ground, number of points above a specific height threshold, etc.). Area-based canopy metrics are used to characterize the three-dimensional (3-D) structure of the vegetation canopies. List of LiDAR-Derived Canopy Height, Canopy Density, and Stem Metric Categories: (Based on G.W. Frazer LiDAR Metrics for Calvert / Hecate Island Acquisition 2012 / 2014 metadata document.) Canopy Height Metrics Canopy Density Metrics Percentiles of Laser Canopy Height (LHQ) Bands Canopy Density at Fractional Canopy Heights (CCF) Bands Diagnostic Bands Tree-Top Bands For a full metadata report on LiDAR acquisition please contact data@hakai.org
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".