Land cover classification of active fire and burned area detections for Canadian provinces, 2001-2010.
Bibliographic record
Abstract
This thesis is a methodological analysis of fire locations in Canadian provinces from 2001 to 2010. The research presented in this thesis highlights the dominant fire types for each province. Accurately locating active fires and burned area is critical to improving emissions estimates of greenhouse gases and black carbon in northern latitudes. Black carbon and emissions are climate changers. Continual release of emissions from a source location has been shown to alter the atmosphere near the source. Black carbon, or soot ash, deposited on arctic snow and ice leads to faster deterioration of the snow and ice. Detected fires and burned areas are recorded by the MODIS satellite sensor on-board the geo-synchronous orbiting Terra and Aqua satellite platforms. The Introduction and Present Study sections introduce the topic. Satellite data and imagery greatly increase accuracy of emissions estimates and aid emergency response teams and hazard monitoring situations. Infrared sensors onboard the Aqua and Terra satellites allow scientists, emergency planners, and citizens to monitor fires that may be hazardous to their lives, property, and families. The MODIS sensor also allows us the unique perspective of spatially locating fires and their areal extent. The Data section describes the technological specifications of the three remote sensing products: MODIS Active Fire Product, MODIS Burned Area Product, and MODIS Land Cover Dataset. The Literature Review section situates this thesis into its historical perspective. Remote sensing is a new science; new techniques are being developed daily. This exciting new science allows researchers to study the specific wavelengths of light that are not visible to the naked eye. The Methodology section justifies the use of the techniques used in this project and presents a past study that was conducted to test the various products available in order to produce the most accurate picture of what is occurring on the ground. The Results and Conclusions present the spatial and temporal distributions of fires in Canadian Provinces from 2001 to 2010. Emergency response units and researchers can use this research to plan for future fire events. This research is also a first step in producing emissions estimates for the region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".