Impact of landscape design with nature-based solutions on microclimate conditions: field measurement study
Bibliographic record
Abstract
Climate change has increased the frequency and intensity of heat waves, placing Canadians at greater risk of heat-related health issues. It has also intensified thermal loads on building envelope systems, resulting in higher cooling energy demands in buildings. Landscape design and urban planning play important roles in shaping urban morphology and regulating urban microclimates, thereby improving outdoor and indoor thermal comfort as well as building energy efficiency. Understanding heat, air, and moisture (HAM) transfer phenomena in urban environments is essential for developing effective landscape design strategies that regulate microclimates and support climate-resilient built environment. The HAM transfer phenomena in urban areas and their impacts on landscape design can be investigated through numerical simulations or field measurements. Field measurements are particularly valuable because they help validate numerical models, which can subsequently be used to evaluate urban thermal performance under different landscape and urban design scenarios. Furthermore, field measurements provide valuable insights for landscape architects and urban planners by assessing how landscape elements and urban morphology influence the urban thermal environment. In this report presents an urban microclimate field measurement study conducted at the NRC’s Montreal Road campus located in Ottawa. The microclimate conditions were monitored at different locations on the campus, each featuring distinct landscape features that reflect different NBS strategies. The microclimate data, including temperature, relative humidity, wind speed and direction, and solar radiation, were collected throughout the summer of 2024. The data were analyzed to investigate the impact of different landscape features on providing adequate thermal comfort for pedestrians. The data collected from this work and presented in this report will serve as a benchmark for validating microclimate simulation models and evaluating different design scenarios aimed at enhancing pedestrian comfort across the campus.
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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 | 0.001 |
| 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 | 0.000 | 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".