Comparison of L3JRC and MODIS global burned area products from 2000 to 2007
Bibliographic record
Abstract
As a significant source of trace gases and particulate matter to the atmosphere, biomass burning plays an important role in climate change and atmospheric chemistry at regional and global scales. The burned area is a critical parameter in estimating fire emissions. Recently, multiyear global burned area products with medium spatial resolution (1 km or 500 m) have been released, including the L3JRC product and the Collection 5 Moderate‐Resolution Imaging Spectroradiometer (MCD45A1) product. In this study, we compare the spatial distribution and temporal pattern of L3JRC and MCD45A1 burned areas over 7 fire years from 1 April 2000 to 31 March 2007. For these 7 fire years, L3JRC gave global burned areas of 3.89, 4.32, 3.53, 4.43, 3.81, 3.60, and 4.51 million km 2 , and MCD45A1 gave values of 3.44, 3.33, 3.57, 3.38, 3.52, 3.39, and 3.61 million km 2 , respectively. The L3JRC product showed persistent burning activity from April to October, whereas the burned area according to MCD45A1 often peaked in August and December at the global scale. For most continents, the L3JRC and MCD45A1 burned areas compared very well during the fire season; however, for the period outside the fire season, L3JRC generally reported a significantly larger burned area than did MCD45A1. The burned areas were examined according to the main vegetation classes given by the GlobCover product. Validation of the L3JRC and MCD45A1 burned areas was performed using data from ground‐based measurements in Canada, the United States, Russia, and China. The results showed that MCD45A1 was more comparable to reference data, although it often underestimated in the boreal forests. L3JRC generally exhibited significant overestimation in these areas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".