TY - JOUR

T1 - Influence of landscape features on urban land surface temperature: scale and neighborhood effects

AU - Shi, Yi

AU - Liu, Shuguang

AU - Yan, Wende

AU - Zhao, Shuqing

AU - Ning, Ying

AU - Peng, Xi

AU - Chen, Wei

AU - Chen, Liding

AU - Hu, Xijun

AU - Fu, Bojie

AU - Kennedy, Robert

AU - Lv, Yihe

AU - Liao, Juyang

AU - Peng, Chungliang

AU - Rosa, Isabel

AU - Roy, David

AU - Shen, Shouyun

AU - Smith, Andy

AU - Wang, Chen

AU - Wang, Zhao

AU - Xiao, Li

AU - Yang, Lu

AU - Yuan, Wenping

AU - Yi, Min

AU - Zhang, Hankui

AU - Zhao, Meifang

AU - Zhu, Yu

AU - Xiao, Jingfeng

PY - 2021/6/1

Y1 - 2021/6/1

N2 - 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 (Eendo) on LST can be described consistently across all cities as a nonlinear function of grain size (gs) and neighbor size (ns) (Eendo = βnsgs-0.5, where β is a city-specific constant) while the influence of exogenous features (Eexo) depends only on neighbor size (ns) (Eexo = γ-εns0.5, 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 (Eendo > Eexo if ns > kgs2/5, where k is a city-specific parameter; otherwise, Eendo < Eexo). 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.

AB - 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 (Eendo) on LST can be described consistently across all cities as a nonlinear function of grain size (gs) and neighbor size (ns) (Eendo = βnsgs-0.5, where β is a city-specific constant) while the influence of exogenous features (Eexo) depends only on neighbor size (ns) (Eexo = γ-εns0.5, 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 (Eendo > Eexo if ns > kgs2/5, where k is a city-specific parameter; otherwise, Eendo < Eexo). 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.

KW - Urban heat island

KW - Neighbor landscape features

KW - Scale dependence

KW - Landscape composition

KW - Ridge regression

U2 - https://doi.org/10.1016/j.scitotenv.2021.145381

DO - https://doi.org/10.1016/j.scitotenv.2021.145381

M3 - Article

VL - 771

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

M1 - 145381

ER -