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.
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References
Blocken, B., & Carmeliet, J. (2004). Pedestrian wind environment around buildings: Literature review and practical examples. Journal of Building Physics, 280402(107), 1097–1963.
Edward, N. (2009). Policies and technical guidelines for urban planning of high-density cities – Air ventilation assessment (AVA) of Hong Kong. Building and Environment, 2009(7), 1478–1488.
Guo, H., & Zhan, Q. (2015). Optimization of wind environment of cognitive space based on space syntax and computer numerical simulation. The Planner, 2015(s1), 300–305.
Koenderink, J. J., & van Doorn, A. J. (1992). Surface shape and curvature scales. Image and Vision Computing, 10, 557–564.
Qian, Y., Shang, T., Zhan, Q., Bo, L., & Yin, J. (2014). Research on outdoor wind environment of building groups based on computer simulation. Computer Modelling & New Technologies 2014, 18(10), 362–369.
Stewart, I. D. (2011). A systematic review and scientific critique of methodology in modern urban heat island literature. International Journal of Climatology, 31(2), 200–217.
Stone, B., Vargo, J., & Habeeb, D. (2012). Managing climate change in cities: Will climate action plans work? Landscape and Urban Planning, 107(3), 263–271.
Wang, J., Zhan, Q., & Xiao, Y. (2015). Hierarchical climate zone as a tool for spatial planning – Case study of Wuhan, China. The International Conference on Computers in Urban Planning and Urban Management 2015.
Wang, J., Zhan, Q., & Guo, H. (2016a). The morphology, dynamics and potential hotspots of land surface temperature and a local scale in urban areas. Remote Sensing, 8, 18.
Wang, J., Zhan, Q., & Xiao, Y. (2016b). Identifying the local surface urban heat island through the morphology of the land surface temperature. The ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, eISSN:2194–9050, III-2, 69–75.
Wang, J., Zhan, Q., & Xiao, Y. (2016c). Identifying the local surface urban heat island through the morphology of the land surface temperature. The ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, eISSN: 2194-9050, III-2, 69–75.
Yashimata, S. (1990). The urban climate of Tokyo. Geographical Review of Japan, 63(1), 98–107.
Yin, J., & Zhan, Q. (2016). The relationship between ventilation and urban morphology based on the method of morphology – Taking Wuhan as an example. Environmental Protection, 44(22), 59–63, 2016.
Zhan, Q., Ouyang, W., Jin, Z., & Zhang, L. (2015). RS and GIS based ventilation potential study and planning. Planners, 2015(11), 95–99.
Zhan, Q., Lan, Y. Ouyang, W. Jin, Z. & Zhang, L. (2016). Study on the planning response of urban wind paths. Proceedings of Annual National Planning Conference of China, Part 4, 2016.
Acknowledgment
This research is supported by the National Natural Science Foundation of China (No. 51378399 and No. 41331175).
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Zhan, Q., Fan, Y., Xiao, Y., Ouyang, W., Yue, Y., Lan, Y. (2018). Urban Wind Path Planning Based on Meteorological and Remote Sensing Data and GIS-Based Ventilation Analysis. In: Shen, Z., Li, M. (eds) Big Data Support of Urban Planning and Management. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-51929-6_21
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DOI: https://doi.org/10.1007/978-3-319-51929-6_21
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