OPEN ACCESS
The irrational layout of urban space is very likely to produce urban heat island (UH). Thus, it is highly necessary to explore how the evolution and spatial distribution of urban network affect the urban wind and heat environment (W&HE). In this paper, an improved genetic algorithm (GA) is proposed to simulate the evolution of urban network, and the UH intensities (UHIs) of Changsha, China are monitored at 18 urban and 7 suburban observation points. On this basis, the author analysed the impacts of urban spatial layout on the W&HE and the UHI. The results show that: the improved GA is feasible for simulation and analysis of the evolution trend of urban network; the UH effect increased with the total urban area and building floor-area ratio (FAR); the mean daytime UHI in downtown Changsha decreased with the growth in green space ratio and increased with the growth in the hardened ground ratio. Therefore, the urban spatial layout should be planned rationally to control the development intensity, lower the ratio of hardened ground and expand the green space in the urban area. The research findings lay a solid theoretical basis for the optimal design of urban layout and the improvement of urban W&HE.
urban network, urban space, wind and heat environment (W&HE), urban heat island (UH) effect, improved genetic algorithm (GA), backpropagation neural network (BPNN)
Steeneveld G. J., Koopmans S., Heusinkveld B. G., Hove L. W. A. V., Holtslag A. A. M. (2011). Quantifying urban heat island effects and human comfort for cities of variable size and urban morphology in the Netherlands. Journal of Geophysical Research Atmospheres, Vol. 116, No. D20. https://doi.org/10.1029/2011jd015988
Gobakis K., Kolokotsa D., Synnefa A., Saliari M., Giannopoulou K., and Santamouris M. (2011). Development of a model for urban heat island prediction using neural network techniques. Sustainable Cities and Society, Vol. 1, No. 2, pp. 104-115. https://doi.org/10.1016/j.scs.2011.05.001
Xie Q., Zhou Z. (2015). Impact of urbanization on urban heat island effect based on tm imagery in wuhan, china. Environmental Engineering & Management Journal, Vol. 14, No. 3, pp. 647-655. https://doi.org/10.30638/eemj.2015.072
Ashtiani A., Mirzaei P. A., Haghighat F. (2014). Indoor thermal condition in urban heat island: Comparison of the artificial neural network and regression methods prediction. Energy & Buildings, Vol. 76, No. 11, pp. 597-604. https://doi.org/10.1016/j.enbuild.2014.03.018
Johnson C. (2015). Green networks: A solution to the urban heat island effect. Sustainable City, pp. 205-214. https://doi.org/10.2495/sc150191
Steeneveld G. J., Koopmans S., Heusinkveld B. G., Theeuwes N. E. (2014). Refreshing the role of open water surfaces on mitigating the maximum urban heat island effect. Landscape & Urban Planning, Vol. 121, No. 1, pp. 92-96. https://doi.org/10.1016/j.landurbplan.2013.09.001
Mohan M., Kikegawa Y., Gurjar B. R., Bhati S., Kolli N. R. (2013). Assessment of urban heat island effect for different land use–land cover from micrometeorological measurements and remote sensing data for megacity delhi. Theorectical & Applied Climatology, Vol. 112, No. 3-4, pp. 647-658. https://doi.org/10.1007/s00704-012-0758-z
Theeuwes N. E., Steeneveld G., Ronda R. J., Holtslag A. A. M. (2016). A diagnostic equation for the daily maximum urban heat island effect for cities in northwestern Europe. International Journal of Climatology, Vol. 37, No. 1, pp. 443-454. https://doi.org/10.1002/joc.4717
Agarwal M., Tandon A. (2010). Modeling of the urban heat island in the form of mesoscale wind and of its effect on air pollution dispersal. Applied Mathematical Modelling, Vol. 34, No. 9, pp. 2520-2530. https://doi.org/10.1016/j.apm.2009.11.016
Takebayashi H. (2011). Study on urban heat island measure effects by the wind exchange in the urban area using upper weather data. Journal of Environmental Engineering, Vol. 76, No. 660, pp. 195-199. https://doi.org/10.3130/aije.76.195
Zheng T., Lau K. L., Ng E. (2016). Urban tree design approaches for mitigating daytime urban heat island effects in a high-density urban environment. Energy & Buildings, Vol. 114, pp. 265-274. https://doi.org/10.1016/j.enbuild.2015.06.031
Rajagopalan P., Lim K. C., Jamei E. (2014). Urban heat island and wind flow characteristics of a tropical city. Solar Energy, Vol. 107, No. 9, pp. 159-170. https://doi.org/10.1016/j.solener.2014.05.042
Lee D. O. (1979). The influence of atmospheric stability and the urban heat island on urban-rural wind speed differences. Atmospheric Environment, Vol. 13, No. 8, pp. 1175-1180. https://doi.org/10.1016/0004-6981(79)90042-8
Mochida A., Lun I. Y. F. (2008). Prediction of wind environment and thermal comfort at pedestrian level in urban area. Journal of Wind Engineering & Industrial Aerodynamics, Vol. 96, No. 10, pp. 1498-1527. https://doi.org/10.1016/j.jweia.2008.02.033
Ookaa R., Hong C., Katoa S. (2008). Study on optimum arrangement of trees for design of pleasant outdoor environment using multi-objective genetic algorithm and coupled simulation of convection, radiation and conduction. Journal of Wind Engineering & Industrial Aerodynamics, Vol. 96, No. 10, pp. 1733-1748. https://doi.org/10.1016/j.jweia.2008.02.039
Lim J., Ooka R. (2014). Building arrangement optimization for urban ventilation potential using genetic algorithm and CFD simulation. Memórias Do Instituto Oswaldo Cruz, Vol. 102, No. 2, pp. 209-213. https://doi.org/10.22260/isarc2014/0033
Isaac L., Akashi M., Kiyoshi S. (2008). Heat balance analysis for management and design of urban environment. Hkie Transactions, Vol. 15, No. 3, pp. 13-23. https://doi.org/10.1080/1023697x.2008.10668120
Takebayashi H., Yamada T., Moriyama M. (2011). Effects of characteristics of urban block on wind environment in the street canyon. Journal of Environmental Engineering, Vol. 76, No. 670, pp. 1087-1092. https://doi.org/10.3130/aije.76.1087