Multi‐year circumpolar assessment of the area burnt in boreal ecosystems using SPOT‐VEGETATION
Bibliographic record
Abstract
The Russian Academy of Sciences' Space Research Institute has developed a new burnt area mapping method and a five‐year database to estimate biomass burning in the Earth's entire boreal region. The mapping method involved SPOT‐VEGETATION time‐series data analysis to detect inter‐annual vegetation changes combined with MODIS hot‐spot data to distinguish fire‐related changes from other types of disturbances. The burnt area database actually covers the boreal biome for the period 2000–2004 with 1 km spatial resolution and 10‐day time frequency, while an automatic data processing chain allows this database to be updated continuously. The accuracy assessment involved comparison with Landsat‐ETM+ derived burnt area estimates for Northern Eurasia and ground data for Canada. This Letter describes the satellite sensor data processing method and the results of the accuracy assessment of the burnt area database and provides burnt area statistics for the boreal region countries.
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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 | 0.001 | 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 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".