A Review of Urban Heat Island formation over changing climate and its impacts on Urban Land Use and Environments and Adaptation Measures

Abstract

Climate change and associated global warming adversely impact urban environments, which leads to the increasing of land surface temperature (LST) and the formation of urban heat islands (UHI). In this study, the author has attempted to present current understandings of UHI formation over changing climate and its probable impacts on urban land use and environmental risks. The review provides a thorough understanding of the UHI and how this impacts urban communities, land use, and environments. In addition, the author has also addressed the quantification process of UHI in the Geospatial platform which helps monitor, assess, and predict the environmental risks at a local scale. The study demonstrated the advantages of earth observation data and Geo-Spatial technologies to detect and monitor the UHI over the temporal scale and a clear understanding of spatial data processing for quantification of UHI. The author finally suggested some best possible adaptation measures of UHI that can assist urban planners and policy makers to build resilient urban communities.

Keywords

• Urban heat islands
• Land surface temperature
• Geo-spatial technologies
• Urban resilience
• Environmental risks
• Adaptation

References

1. Arnfield, A.J. (2003). Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. International journal of climatology, 23 (1), 1-26.
2. Artis, D.A. and Carnahan, W.H. (1982). Survey of emissivity variability in thermography of urban areas, Remote Sensing of Environment, 12 (4), 313–329.
3. Blocken, B., Stathopoulos, T., and Carmeliet, J. (2007). CFD simulation of the atmospheric boundary layer: wall function problems. Atmospheric environment, 41 (2), 238-252.
4. Brivio, P.A., Lechi, G., and Zilioli, E. (2006). Principles and methods ditelerilevamento, CittàStudiEdizioni, to Turin, 449-479.
5. Carlson, T.N. and Ripley, D.A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index, Remote Sensing of Environment, 62 (3), 241–252.
6. Caselles, V., Coll, C., and Valor, E. (1997). Land surface emissivity and temperature determination in the whole HAPEX–Sahel area from AVHRR data, International Journal of Remote Sensing, 18, 1009–1027.
7. Choudhury, B.J., Dorman, T.J., and Hsu, A.Y. (1995). Modeled and observed relations between the AVHRR split window temperature difference and atmospheric precipitable water over land surfaces, Remote Sensing of Environment, 51, 281-290.
8. Chrysoulakis, N., Kamarianakis, Y., Xu, L., Mitraka, Z., and Ding, J. (2008). Combined use of MODIS, AVHRR and radiosonde data for the estimation of spatiotemporal distribution of precipitable water, J. Geophys. Res., 113, D05101.

9. Coll, C., Caselles, V., Sobrino, J. A., and Valor, E. (1994). On the atmospheric dependence of the split window equation for land surface temperature. International Journal of Remote Sensing, 15, 105–122.
10. Giannini, M. B., Belfiore, O. R., Parente, C., and Santamaria, R. (2015). Land Surface Temperature from Landsat 5 TM images: comparison of different methods using airborne thermal data, Journal of Engineering Science and Technology Review, 8 (3), 83-90.
11. Khan, A. and Chatterjee, S. (2016). Numerical simulation of urban heat island intensity under urban–suburban surface and reference site in Kolkata, India, Model. Earth Syst. Environ., 2:71. DOI 10.1007/s40808-016-0119-5.
12. Liu, C., Shi, B., Tang, C., and Gao, L. (2011). A numerical and field investigation of underground temperatures under Urban heat island. Build Environ., 46 (5), 1205–1210.
13. Marko, K., Zulkarnain, F., and Kusratmoko, E. (2016). Coupling of Markov chains and cellular automata spatial models to predict land cover changes (case study: upper CiLeungsi catchment area), IOP Conf. Ser.: Earth Environ. Sci., 47, 012032 (http://iopscience.iop.org/1755-1315/47/1/012032).
14. Oke, T. R. (1973). City size and the urban heat island. Atmospheric Environment, 7 (8), 769-779.
15. Oke, T.R. and Maxwell, G.B. (1975). Urban heat island dynamics in Montreal and Vancouver. Atmospheric Environment, 9 (2), 191-200.
16. Pickett, S.T., Cadenasso, M.L., Grove, J.M., Nilon, C.H., Pouyat, R.V., Zipperer, W.C., and Costanza, R. (2008). Urban ecological systems: linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas, Urban Ecology, 99-122.
17. Policy Pointer No. 2. (2013). Responding to Urban Heat Island Effects, Asian Cities Adapt., 1-2.
18. Prasad, R. (2017). The urban heat island effect - Rapid urbanisation increases temperatures, The Hindu, [Accessed: December 19]. http://www.thehindu.com/opinion/oped/the-urban-heat-island effect/article21860626.ece.
19. Rose, A.L. and Devadas, M.D. (2005). Effects Of Changing Landuse Patterns On Urban Heat Island In Chennai, World Sustainable Building Conference, Tokyo (SB05Tokyo), 27-29 September, 3949-3952.
20. Saunders, R.W. and Kriebel, K.T. (1988). An improved method for detecting clear sky and cloudy radiances from AVHRR data, International Journal of Remote Sensing, 9, 123–150.
21. Snyder, W. C., Wan, Z., Zhang, Y., and Feng, Y.Z. (1998). Classification based emissivity for land surface temperature measurement from space, International Journal of Remote Sensing, 19 (14), 2753–2774.
22. Sobrino, J. A., Caselles, V., and Becker, F. (1990). Significance of the remotely sensed thermal infrared measurements obtained over a citrus orchard, ISPRS Photogrammetric Engineering and Remote Sensing, 44 (6), 343–354.
23. Sobrino, J. A., Jiménez-Muñoz, J. C., and Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5, Remote Sensing of Environment, 90 (4), 434–440.
24. Stathopoulou, M., Cartalis, C., and Keramitsoglou, I. (2004). Mapping micro-urban heat islands using NOAA/AVHRR images and CORINE land cover: an application to coastal cities of Greece International Journal of Remote Sensing, 25 (12), 2301–2316.
25. Yang, L. (2014). Green Building Design: Wind Environment of Building. Shanghai: Tongji University Press.
26. Zha, Y., Gao, J., and Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery, International Journal of Remote Sensing, 24 (3), 583-594.