Identification of the urban heat islands phenomenon in a small city: the study case of Três Rios/RJ, Brazil
Bibliographic record
Abstract
The phenomenon of urban heat islands (UHI) is caused by the increase in temperatures of an urban area as a result of the development of human activities within that area, this phenomenon is usually studied in medium and large cities. This study aims to verify if the phenomenon of UHI occurs in the municipality of Três Rios – RJ, a small sized city. This study included the use of mobile transect, through pre-established data collection points/stations. Five data collection points were selected, from which one was included in a rural area, one in the Parque Natural Municipal (Urban Park, within the city), and three points within the urbanized area. The equipment used was the Brunton® / ADC PRO handheld weather station. The data collection period ranged from September 2018 until July 2019, which included the four seasons. Measurements were taken at 6:00, 12:00, 15:00, 18:00, and 21:00h, in alternate days during the study period. Considering the temperature measurements, two different indicators of thermal variability were used. Strong magnitude heat islands were detected, taking into consideration the relevant variation of maximum temperatures observed in the urban area when compared to the rural area. The results indicate the most affected populations to be the ones located within urban areas, mostly individuals under socioeconomic vulnerability. The results obtained can be used as support for the development of strategies to minimize the thermal discomfort to populations exposed to the influence of higher magnitude urban heat islands.
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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 | 0.001 |
| 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".