Street-level surface and air temperatures in the Urban Center of Málaga, Spain
Bibliographic record
Abstract
Increasing urbanization is leading to rising temperatures in cities, especially in their central areas, where artificial covers, street canyons and human-induced heat release are more common. This urban microclimate is especially critical in historical centers, as the protection of these areas' cultural assets hinders the introduction of adaptation measures. In this context, this study developed a methodology to characterize the microclimate in historical city centers, using the Mediterranean city of Málaga in southern Spain as a paradigmatic case study. To this end, field measurements were carried out by using a bicycle mobile station and a handheld thermal imaging camera along the so-called Picassian route, covering eleven different streets and eight historical buildings (eleven façades) where air and surface temperatures were collected. The results showed significant differences in the values of air and surface temperatures, so studies of urban microclimate should consider both types of temperatures together, and especially the temperature of building façades, which is often ignored due to the lack of open data about it but has notable different patterns. An analysis of the relationship between field data and a range of spatial factors related to the morphology and surface artificiality of urban areas revealed that shading and tree planting might provide a solution to heat mitigation. For historical centers with important space constraints, these solutions may consist of installing awnings and green façades. • The urban microclimate was characterized using mobile and thermal imaging records. • Field data on air and surface (pavement and façade) temperature were collected. • Air, pavement and façade temperatures were positively correlated to each other. • There were significant differences in the values of air and surface temperatures. • Shading and vegetation were the factors showing more potential for heat reduction. • Awnings and green facades are recommended in historical centers with limited space.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 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".