Influence of landscape features on urban land surface temperature: Scale and neighborhood effects

Yi Shi; Shuguang Liu; Wende Yan; Shuqing Zhao; Ying Ning; Xi Peng; Wei Chen; Liding Chen; Xijun Hu; Bojie Fu; Robert Kennedy; Yihe Lv; Juyang Liao; Chunliang Peng; Isabel M D Rosa; David Roy; Shouyun Shen; Andy Smith; Cheng Wang; Zhao Wang; Li Xiao; Jingfeng Xiao; Lu Yang; Wenping Yuan; Min Yi; Hankui Zhang; Meifang Zhao; Yu Zhu

doi:10.1016/j.scitotenv.2021.145381

Influence of landscape features on urban land surface temperature: Scale and neighborhood effects

Sci Total Environ. 2021 Jun 1:771:145381. doi: 10.1016/j.scitotenv.2021.145381. Epub 2021 Jan 27.

Authors

Yi Shi¹, Shuguang Liu², Wende Yan¹, Shuqing Zhao³, Ying Ning¹, Xi Peng¹, Wei Chen¹, Liding Chen⁴, Xijun Hu⁵, Bojie Fu⁴, Robert Kennedy⁶, Yihe Lv⁴, Juyang Liao⁷, Chunliang Peng⁷, Isabel M D Rosa⁸, David Roy⁹, Shouyun Shen⁵, Andy Smith⁸, Cheng Wang¹⁰, Zhao Wang¹, Li Xiao¹, Jingfeng Xiao¹¹, Lu Yang³, Wenping Yuan¹², Min Yi¹³, Hankui Zhang¹⁴, Meifang Zhao¹, Yu Zhu¹

Affiliations

¹ College of Life Science and Technology, National Engineering Laboratory for Applied Technology in Forestry & Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China.
² College of Life Science and Technology, National Engineering Laboratory for Applied Technology in Forestry & Ecology in South China, Central South University of Forestry and Technology, Changsha 410004, China. Electronic address: shuguang.liu@csuft.edu.cn.
³ Peking University, Beijing 100871, China.
⁴ Center for Ecological Research, Chinese Academy of Sciences, Beijing 100085, China.
⁵ College of Landscape Architecture, Central South University of Forestry and Technology, Changsha 410004, China.
⁶ Geography, Environmental Sciences, and Marine Resource Management, Oregon State University, Corvallis, OR 97331, United States of America.
⁷ Hunan Forest Botanical Garden, Changsha 410116, China.
⁸ School of Natural Sciences, Bangor University, Gwynedd LL57 2UW, UK.
⁹ Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI 48824, United States of America.
¹⁰ Chinese Academy of Forestry, Beijing 100091, China.
¹¹ Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, United States of America.
¹² School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Zhuhai Key Laboratory of Dynamics Urban Climate and Ecology, Sun Yat-sen University, Zhuhai 510245, China.
¹³ Ecology and Environment Department of Hunan Province, Changsha 410014, China.
¹⁴ Department of Geography and Geospatial Sciences, Geospatial Sciences Center of Excellence, South Dakota State University, Brookings, SD 57007, United States of America.

PMID: 33548722
DOI: 10.1016/j.scitotenv.2021.145381

Abstract

Higher land surface temperature (LST) in cities than its surrounding areas presents a major sustainability challenge for cities. Adaptation and mitigation of the increased LST require in-depth understanding of the impacts of landscape features on LST. We studied the influences of different landscape features on LST in five large cities across China to investigate how the features of a specific urban landscape (endogenous features), and neighboring environments (exogenous features) impact its LST across a continuum of spatial scales. Surprisingly, results show that the influence of endogenous landscape features (E_endo) on LST can be described consistently across all cities as a nonlinear function of grain size (g_s) and neighbor size (n_s) (E_endo = βn_sg_s^-0.5, where β is a city-specific constant) while the influence of exogenous features (E_exo) depends only on neighbor size (n_s) (E_exo = γ-εn_s^0.5, where γ and ε are city-specific constants). In addition, a simple relationship describing the relative strength of endogenous and exogenous impacts of landscape features on LST was found (E_endo > E_exo if n_s > kg_s^2/5, where k is a city-specific parameter; otherwise, E_endo < E_exo). Overall, vegetation alleviates 40%-60% of the warming effect of built-up while surface wetness intensifies or reduces it depending on climate conditions. This study reveals a set of unifying quantitative relationships that effectively describes landscape impacts on LST across cities, grain and neighbor sizes, which can be instrumental towards the design of sustainable cities to deal with increasing temperature.

Keywords: Landscape composition; Neighbor landscape features; Ridge regression; Scale dependence; Urban heat island.