Estimating forest biomass components with hemispherical photography for Douglas-fir stands in northwest Oregon
Bibliographic record
Abstract
Accurately and quickly identifying inventories of forest biomass has become increasingly important for a variety of reasons. Current allometric equations require time-consuming tree-level measurements, but ground-based remote sensing could lead to faster estimates of forest biomass. Hemispherical photography (HP) is one potential technology that could estimate forest biomass quickly and efficiently. This analysis is based on a study in northwest Oregon where 15 Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) plots were destructively sampled, and 60 HPs (four per plot) were taken. One photograph was taken after removing each quartile of a plot (by basal area). Two subsets of bone-dry biomass were measured and estimated: (i) crown and branch biomass (CBB) and (ii) total aboveground biomass (AGB). AGB ranged from 136 to 423 Mg/ha, and CBB ranged from 26 to 68 Mg/ha. A regression analysis between actual and HP estimated biomass showed that the average of the top two and top three 18° zenith angles resulted in the highest correlation and lowest RMSE for both CBB and AGB, while an estimate of plant area index over the top three zenith angles had the lowest correlation. HP estimates are compared with two allometric equations: one based on a regional study and one based on a national compilation of studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 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".