Reading Microclimates with 3D City Models

Description and use

The author describes using 3D city models combined with climate data to analyze street-level microclimates. Traditional 2D maps fail to show how buildings and materials affect heat and wind. The tool Shapezo allows for quick 3D model generation to assess shade, airflow, and heat islands, enabling better decisions for greening and public space design.

Problem

Traditional 2D urban planning maps fail to capture street-level microclimates, leading to urban heat island effects where built environments trap heat, block wind, and lack adequate shade, making cities uncomfortable and unhealthy during summer heatwaves.

Outcome

The integration of 3D city models with climate data allows for a detailed understanding of microclimates, enabling more effective urban design decisions that improve street-level comfort and mitigate heat island effects.

Workflow

• Identify the urban area of interest on a map.
• Use an AI tool like Shapezo to generate a 3D city model of the region quickly.
• Overlay climate data (temperature, humidity, wind speed, solar exposure) onto the 3D model.
• Analyze the model to identify heat traps, wind-blocked areas, and insufficient shade.
• Evaluate specific design elements such as tree canopy density, paving materials, and building spacing.
• Formulate targeted design interventions (e.g., adding shade on west sides, improving wind corridors).
• Use insights to guide urban design decisions for public spaces, sidewalks, and green infrastructure.

Evidence

For me, the useful way to study that is to combine 3D city models with climate data.

Source

Shapezo is an example of that kind of workflow. The basic idea is simple: I frame a region on a map, and AI generates the model for that area.

Source