Remote Sensing Estimates of Boreal and Temperate Forest Woody Biomass: Carbon Pools, Sources, and Sinks
Bibliographic record
Abstract
The relation between satellite measurements of the normalized difference vegetation index (NDVI), cumulated over the growing season, and inventory estimates of forest woody biomass carbon is estimated statistically with data from 167 provinces and states in six countries (Canada, Finland, Norway, Russia and the USA for a single time period and Sweden for two periods). Statistical tests indicate that the regression model can be used to represent the relation between forest biomass and NDVI across spatial, temporal and ecological scales for relatively long time scales. For the 1.42 billion ha of boreal and temperate forests in the Northern Hemisphere, the woody biomass carbon pools and sinks are estimated at a relatively high spatial resolution (8 8 km). We estimate the carbon pool to be 61 F 20 gigatons (10 ) carbon (Gt C) during the late 1990s and the biomass sink to be 0.68 F 0.34 Gt C/year between the 1982 and 1999. The geographic detail of carbon sinks provided here can contribute to a potential monitoring program for greenhouse gas emission reduction commitments under the Kyoto Protocol. D 2002 Elsevier Science Inc. All rights reserved.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".