Spatiotemporal trends of urban heat island effect along the urban development intensity gradient in China
| Authors: | Decheng Zhou, Liangxia Zhang, Lu Hao, Ge Sun, Yongqiang Liu, Chao Zhu |
| Year: | 2016 |
| Type: | Scientific Journal |
| Station: | Southern Research Station |
| DOI: | https://doi.org/10.1016/j.scitotenv.2015.11.168 |
| Source: | Science of The Total Environment |
Abstract
Urban heat island (UHI) represents a major anthropogenic modification to the Earth system and its relationshipwith urban development is poorly understood at a regional scale. Using AquaMODIS data and LandsatTM/ETM+images, we examined the spatiotemporal trends of the UHI effect (ΔT, relative to the rural reference) along theurban development intensity (UDI) gradient in 32 major Chinese cities from 2003 to 2012. We found that thedaytime and nighttime ΔT increased significantly (p b 0.05, mostly in linear form) along a rising UDI for 27and 30 out of 32 cities, respectively. More rapid increases were observed in the southeastern and northwesternparts of China in the day and night, respectively. Moreover, the ΔT trends differed greatly by season and duringdaytime in particular. The ΔT increased more rapidly in summer than in winter during the day and the reverseoccurred at night for most cities. Inter-annually, the ΔT increased significantly in about one-third of the citiesduring both the day and night times from 2003 to 2012, especially in suburban areas (0.25 b UDI ≤ 0.5), with insignificanttrends being observed for most of the remaining cities.We also found that the ΔT patterns along the UDIgradient were largely controlled by local climate-vegetation conditions, while that across years were dominatedby human activities. Our results highlight the strong and highly diverse urbanization effects on local climate crossChina and offer limitations on how these certain methods should be used to quantify UHI intensity over largeareas. Furthermore, the impacts of urbanization on climate are complex, thus future research efforts should focusmore toward direct observation and physical-based modeling to make credible predictions of the effects.