Requirements for space-based observations in fire management: a report by the Wildland Fire Hazard Team, Committee on Earth Observation Satellites (CEOS) Disaster Management Support Group (DMSG)
Bibliographic record
Abstract
The Wildland Fire Hazard Team reviewed potential requirements for space-based observations in fire management. The team produced a report, developed under the auspices of the Disaster Management Support Group (DMSG) of the G-7 Committee on Earth Observation Satellites (CEOS). The document was prepared by an international working group, with experience in the field of remote sensing as applied to wildland fire management. The team identified seven major requirements. (http://disaster.ceos.org/2000Ceos/progress/reports/fire.html) These requirements could substantially improve wildland fire management programs, should CEOS augment existing satellites or develop new Earth observation satellites as recommended. The requirements address the different temporal, spatial, and spectral characteristics needed in different phases of fire management and geographic areas of interest. These requirements include fuel mapping, risk assessment, detection, monitoring, mapping, burned area recovery, and smoke management. They are supported by 10 recommendations, as outlined in this paper.
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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 | 0.037 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".