In this study, we assess the urban heat island (UHI) effect using remote sensing data, a phenomenon emerging under the background of global warming and urbanization. With the rapid development of satellite technology, remote sensing images are widely applied to evaluate the UHI effect on rapidly-urbanized areas in recent years. In the study, we applied Landsat 8 data to estimate the land surface temperature (LST) in the case study of Shenzhen and Hong Kong. The methods of the mono-window algorithm (MWA), single-channel method (SCM), Qin’s split-window algorithm (SWA-Q) and Sobrino’s split-window algorithm (SWA-S) are used to calculate the LST from Landsat 8 data on 29 November 2013, 16 November 2014, 18 October 2015, and 7 February 2016. The results show that LST retrievals by SWA-Q are better than those of the other algorithms in the case study of Shenzhen and Hong Kong. From 2013 to 2016, the high-LST zones or UHIs in Shenzhen and Hong Kong are substantially identical. Although the LST is not obviously correlated with vegetation distribution, the growth condition of vegetation may impact the distribution of the UHI, and the high LST is slightly correlated to the high atmospheric particulate concentration. Additionally, in general, Shenzhen and Hong Kong are weak UHI regions and the UHI-affected area in Shenzhen is larger than that in Hong Kong from 2013 to 2016.
This is an open access article distributed under the Creative Commons Attribution License
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited