Urban Wind Corridors Analysis via Network Theory

Abstract

We develop a new model for urban wind corridors analysis and detection of urban wind ventilation potential based on concepts and principles of network theory. Our approach is based solely on data extracted from spatial urban features that are easily obtained from a 3D model of the city. Once the spatial features have been extracted, we embed them onto a graph topology. This allows us to use theories and techniques of network theory, and in particular graph theory. Utilizing such techniques, we perform end-to-end network flow analysis of the wind potential across the city and, in particular, estimate the locations, strengths, and paths of the wind corridors. To calibrate our model, we use a dataset generated by a meso-scale climate model and estimate the model parameters by projecting the wind vector field of the climate model onto a graph, thus providing a meaningful comparison of the two models under a new metric. We illustrate our modeling approach on the city of Singapore and explain how the results are useful for climate-informed urban design.

Keywords

• urban canopy wind
• visual data processing
• meso-scale climate simulation
• network theory
• graph theory
• Least Cost Path (LCP)