Abstract
Urbanization and aging of society are two converging trends of current demographic changes. The intensified human activities associate with the formation and dynamic of Urban Heat Island (UHI) which is harmful to health. Looking into the correlation between UHI effect and the land surface coverage of everyday spaces is curtail and significant. Aided by spatial analysis and spatial statistic functions based on Geographical Information System (GIS) and data extraction and processing methods enabled by the Remote Sensing (RS) platform, this paper detected the distribution of land surface temperature and traced its changes alongside dynamics of land surface coverage in the selected typical areas of Hong Kong. Findings of this paper will be significant for Hong Kong planners, architects and housing officials to consider when deciding on the next step of Hong Kong urban planning and housing development.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Resource: Hong Kong Population by Census 2016. http://www.bycensus2016.gov.hk/tc/bc-dp.html
- 2.
Resource: Hong Kong 2016: The Fact. https://www.yearbook.gov.hk/2016/en/pdf/Facts.pdf
References
Chun, B., Guldmann, J.-M.: Spatial statistical analysis and simulation of the urban heat island in high-density central cities. Landsc. Urban Plan. 125, 76–88 (2014)
Deng, W.: The new town development and planning in Hong Kong. Urban Plann. Int. (4), 7–11 (1995)
Giridharan, R., Lau, S.S.Y., Ganesan, S., Givoni, B.: Urban design factors influencing heat island intensity in high-rise high-density environments of Hong Kong. Build. Environ. 42(10), 3669–3684 (2007). https://doi.org/10.1016/j.buildenv.2006.09.011
Griend, A.A.V.D., Owe, M.: On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Int. J. Remote Sens. 14(6), 1119–1131 (1993). https://doi.org/10.1080/01431169308904400
Hiemstra, J.A., Saaroni, H., Amorim, J.H.: The urban heat island: thermal comfort and the role of urban greening. In: Pearlmutter, D., Calfapietra, C., Samson, R., O’Brien, L., Krajter Ostoić, S., Sanesi, G., Alonso del Amo, R. (eds.) The Urban Forest. FC, vol. 7, pp. 7–19. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-50280-9_2
Kyriakodis, G.E., Santamouris, M.: Using reflective pavements to mitigate urban heat island in warm climates-results from a large scale urban mitigation project. Urban Clim. (2017)
Li, J., Wang, X., Wang, X., Ma, W., Zhang, H.: Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area. China Ecol. Complex. 6(4), 413–420 (2009)
Lillesand, T., Kiefer, R.W., Chipman, J.: Remote Sensing and Image Interpretation. Wiley, Chichester (2014)
Liu, L., Zhang, Y.: Urban heat island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sens. 3(7), 1535–1552 (2011)
Ng, E., Ren, C.: The Urban Climatic Map: A Methodology for Sustainable Urban Planning. Routledge, London (2015)
Qin, Z., Karnieli, A., Berliner, P.: A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Int. J. Remote Sens. 22(18), 3719–3746 (2001)
Santamouris, M.: Energy and Climate in the Urban Built Environment. Routledge, New York (2013)
Stone Jr., B., Rodgers, M.O.: Urban form and thermal efficiency: how the design of cities influences the urban heat island effect. J. Am. Plan. Assoc. 67(2), 186–198 (2001)
Streutker, D.R.: A remote sensing study of the urban heat island of Houston, Texas. Int. J. Remote Sens. 23(13), 2595–2608 (2002). https://doi.org/10.1080/01431160110115023
Weng, Q., Lu, D., Schubring, J.: Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens. Environ. 89(4), 467–483 (2004). https://doi.org/10.1016/j.rse.2003.11.00
Wong, M.S., Peng, F., Zou, B., Shi, W.Z., Wilson, G.J.: Spatially analyzing the inequity of the Hong Kong urban heat island by socio-demographic characteristics. Int. J. Environ. Res. Public Health 13(3), 317 (2016)
Yuan, F., Bauer, M.E.: Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sens. Environ. 106(3), 375–386 (2007). https://doi.org/10.1016/j.rse.2006.09.003
Zhang, J., Wang, Y., Li, Y.: A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6. Comput. Geosci. 32(10), 1796–1805 (2006). https://doi.org/10.1016/j.cageo.2006.05.001
Zhang, Y.: Detection of urban housing development by fusing multisensor satellite data and performing spatial feature post-classification. Int. J. Remote Sens. 22(17), 3339–3355 (2001)
Liu, X.P., Deng, R.R., Peng, X.J.: A fast atmospheric correction method based on TM imagery. Sci. Geogr. Sinica 25(1), 87–93 (2005)
Acknowledgement
This research was supported by the Faculty of Social Science Direct Grant on the project titled “Study of impact of hyper-density housing development on Urban Heat Island of Hong Kong”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Tsou, J.Y., Li, X., Tsou, K., He, J., Pan, D. (2018). Detect Relationship Between Urban Housing Development and Urban Heat Island Dynamic in Hyper-density Hong Kong by Integrating GIS and RS Techniques. In: Smith, I., Domer, B. (eds) Advanced Computing Strategies for Engineering. EG-ICE 2018. Lecture Notes in Computer Science(), vol 10863. Springer, Cham. https://doi.org/10.1007/978-3-319-91635-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-91635-4_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-91634-7
Online ISBN: 978-3-319-91635-4
eBook Packages: Computer ScienceComputer Science (R0)