ACQUISITION AND PROCESSING OF HIGH RESOLUTION HYPERSPECTRALIMAGERIES FOR THE 3D MAPPING OF URBAN HEAT ISLANDS ANDMICROPARTICLES OF MONTREAL
Bibliographic record
Abstract
Abstract. Ville de Montreal wanted to develop a system to identify heat islands and microparticles at the urban scale and to study their formation. UQAM and UdeM universities have joined their expertise under the framework "Observatoire Spatial Urbain" to create a representative geospatial database of thermal and atmospheric parameters collected during the summer months. They innovated in the development of a methodology for processing high resolution hyperspectral images (1–2 m). In partnership with Ville de Montreal, they integrated 3D geospatial data (topography, transportation and meteorology) in the process. The 3D mapping of intraurban heat islands as well as air micro-particles makes it possible, initially, to identify the problematic situations for future civil protection interventions during extreme heat. Moreover, it will be used as a reference for the Ville de Montreal to establish a strategy for public domain tree planting and in the analysis of urban development projects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".