Advertisement

Prediction and Visualization for Urban Heat Island Simulation

  • Bin Shao
  • Mingmin Zhang
  • Qingfeng Mi
  • Nan Xiang
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6758)

Abstract

The simulation and forecast of urban heat island effect was studied. Since the reason for the formation of urban heat island is complex, the current model cannot take all the influence factors into consideration. When a new influence factor is introduced, it will lead to a comprehensive change of the model. In order to solve these problems, the paper provides an urban heat island effect analysis and forecast model based on artificial neural network. The experiment shows the efficiency of this forecast model. Furthermore, the heat island effect information visualization has been carried on in this paper. This prediction model for urban heat island has raised a new idea for the latest achievements of computer technology applications in related fields.

Keywords

urban heat island urban air temperature simulation neural network genetic algorithm information visual 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Jonsson, B.C., Eliassoni, et al.: Suspended particulate matter and its relation to the urban climate in Dares Salaam. Tanzania Atmospheric Environment 38, 4175–4181 (2004)CrossRefGoogle Scholar
  2. 2.
    Kevin, C., Christian, H., Barryl: Estimating the effects of increased urbanization on surface meteorology and ozone concentrations in the New York City metropolitan region. Atmospheric Environment 41, 1803–1819 (2007)CrossRefGoogle Scholar
  3. 3.
    Kim, S.W., Yoon, S.C., Won, G., et al.: Ground-based remote sensing measurements of aerosol and ozone in an urban area: A case study of mixing height evolution and its effects on Ground-level ozone concentrations. Atmospheric Environment 41, 7069–7081 (2007)CrossRefGoogle Scholar
  4. 4.
    Miao, M.: Numerical simulation of the urban heat island over pollutant dispersion. Journal of Atmospheric Science 14(2), 207–214 (1990)Google Scholar
  5. 5.
    Huang, H., Ooka, R., Kato, S.: Urban thermal environment measurements and numerical simulation for an actual complex urban area covering a large district heating and cooling system in summer. Atmospheric Environment 39(34), 6362–6375 (2005)CrossRefGoogle Scholar
  6. 6.
    Chen, X.-L., Zhao, H.-M., Li, P.-X., Yin, Z.-Y.: Remote sensing image-based analysis of relationship between urban heat island and land use/cover changes. Remote Sensing of Environment 104(2), 133–146 (2006)CrossRefGoogle Scholar
  7. 7.
    Priyadarsini, R., Hien, W.N., David, C.K.W.: Microclimatic modeling of the urban thermal environment of Singapore to mitigate urban heat island. Solar Energy 82(8), 727–745 (2008)CrossRefGoogle Scholar
  8. 8.
    Tian, Z.: Analysis of Urban Heat Island and Study on Impact of UHI on Building HAVC Energy Consumption. Tianjin University, PhD thesis 6, 39–69 (2005)Google Scholar
  9. 9.
    Moriyama, M.: Making method of Klimatope map based on normalized vegetation index and one dimensional heat budget model. Journal of Wind Engineering and Industrial Aerodynamics 220 (1999)Google Scholar
  10. 10.
    Mi, X.C., Ma, K.P., Zou, Y.B.: Artificial neural network and its application in agricultural and ecological research. Acta Phytoecologica Sinica 29(5), 863–870 (2005)Google Scholar
  11. 11.
    Holland, J.H.: Adaptation in natural and artificial system, pp. 23–140. University of Michigan Press, Ann Ardor (1975)Google Scholar
  12. 12.
    Zhou, N., Zhang, L.: Method of Information Resources Visualization Model, 8th edn. pp. 37–58. Science Press, Beijing (2008)Google Scholar
  13. 13.
    Zhao, X., et al.: Mathematical Statistics, vol. 9, pp. 70–96. Science Press, Beijing (2002)Google Scholar
  14. 14.
    Man-land system theme database of Institute of Geographic Sciences and Natural Resources Research of Chinese Academy of Sciences (the original database of natural resources) [DB/OL], http://www.data.ac.cn
  15. 15.
    Mi, Q., Zhang, M., Pan, Z.: 3D visualization of adaptive multi-scale UHI simulation based on a computer aided modeling method. Journal of Information & Computational Science 6(5), 2061–2066 (2009)Google Scholar
  16. 16.
    Yang, H., Zhang, H., You, S.: CFD simulation and study on office thermal environment of Airpark. Journal of Shandong Institute of Architecture and Engineering 19(4), 41–52 (2004)Google Scholar
  17. 17.
    Danny, H.W.L., Wont, S.L., Lam, J.C.: Climate effect on cooling load determination in subtropical regions. Energy Conversion & Management 1, 831–843 (2003)Google Scholar
  18. 18.
    Gugliermetti, F., Passerini, G., Bisegna, F.: Climate models for the assessment of office buildings energy performance. Building and Environment 39, 39–50 (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Bin Shao
    • 1
    • 2
  • Mingmin Zhang
    • 2
  • Qingfeng Mi
    • 2
  • Nan Xiang
    • 2
  1. 1.School of Information and EngineeringHuzhou Teachers CollegeHuzhouChina
  2. 2.State Key Laboratory of CAD&CGZhejiang UniversityHangzhouChina

Personalised recommendations