Boreal forest change detection with the spaceborne Geoscience Laser Altimeter System: Wildfires and canopy height changes derived from waveform pairs
Bibliographic record
Abstract
The Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) has provided measurements of vegetation structure and together with upcoming follow-up missions such as ICESat-2, vegetation changes may be studied globally in the near future. In this research project, ICESat’s individual ability to estimate changes in maximum canopy height was evaluated over the boreal forests of northern Alberta, Canada. The changes were estimated from waveform pairs with one and two-year time intervals (2004 to 2006), and although footprint misalignments caused random errors on the order of meters, average decreases in maximum canopy height were observed over wildfires in northern Alberta. Only measurements from the three late-May to late-June campaigns were used since snow cover might have complicated interpretation of the results otherwise. Footprint center distances of waveform pairs were up to 150 m and the upper limit of the standard error of an individual change measurement was estimated at 8 m. Maximum canopy height was estimated to decrease with about one meter on average within wildfire perimeters and the standard error of the mean was estimated at ±0.3 m. Changes in waveform extent were used to estimate the changes in maximum canopy height, and a revised method of delineating the waveform extent is presented. The revision is shown to improve the reproducibility of the waveform extent measurements and is expected to improve the accuracy of change estimation and any biophysical variable retrieval methods that depend on the waveform extent. The attempt made to study canopy changes with the GLAS was successful in detecting changes due to wildfires and has shed light on the many issues involved. With further research on changes in the transmitted laser pulse characteristics and implementation of biophysical variable retrievals, the GLAS may prove to be a valuable tool for studies on global vegetation dynamics.
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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 | 0.000 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".