Urban Wind Path Planning Based on Meteorological and Remote Sensing Data and GIS-Based Ventilation Analysis

Abstract

Improving urban heat environment and air quality by altering urban wind paths is a rising topic in PSS, but it currently lacks quantitative methods and practical framework. This study proposes a systematic approach to supporting urban wind path planning for improving heat environment, using remote sensing images and wind and temperature data from local weather stations, GIS-based building and road data, etc. Local surface urban heat islands (LSUHIs) are identified by retrieving remote sensing data, the knowledge of which is combined with other local knowledge to determine target regions for heat environment improvement. Potential wind paths are determined by natural wind resources and built-up environment: Macroscopic simulation of the city’s wind field with WRF model localizes and quantifies natural wind resources; building density, surface roughness, and road orientation describe morphological factors that influence local ventilation capabilities, including its coherence with and resistance against potential natural winds. With the problematic regions and potential wind paths thus delineated, planning measures can then be correspondingly formulated.