Public Open Space Design Study on the Basis of Microclimate and Spatial Behavior in Hot and Cold Weather Conditions in Downtown Area
Bibliographic record
Abstract
Microclimate in open space affected by the urban layouts and spatial forms plays an important role in the outdoor comfort, thus the outdoor activities based on the comfort sensation will directly affected by the microclimate. An outstanding open space should satisfy different requirements of outdoor activities and create relatively comfortable sensation.Most studies have been conducted on these relationships only above 0 Celsius degree. However, only few have focused on extreme situations in both hot and cold seasons. Therefore, from microclimate perspective, taking people’s comfort and spatial behaviors as criterions, this research discussed how the open space forms affect microclimate, thus affect comfort sensation and spatial behaviors. The outcomes may provide some useful insights for planners and architects to understand the relationship among microclimate, open space and people.Results showed that microclimate obviously affected people’s comfort. In hot season, shade and air-flow played crucial roles in outdoor comfort. People tend to stay outside in the shade and the area with higher air velocity. After sunset is popular period for outdoor activities. In cold season, at the same ambient temperature, lower air velocity raised the comfort level. Shade also had influences on comfort sensation but do not affect spatial behaviors significantly.This paper also proposes optimization design proposals of densely populated open space based on extreme microclimate and spatial behaviour.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".