The spatial configuration of buildings: A vital consideration impossible to ignore in regulating urban land surface temperature? Evidence from 35 Chinese cities

Wei Chen; Jianjun Zhang; Shidong Liu; Sen Liang; Yaping Zhang; Shu Fu

doi:10.1016/j.scitotenv.2022.160946

The spatial configuration of buildings: A vital consideration impossible to ignore in regulating urban land surface temperature? Evidence from 35 Chinese cities

Sci Total Environ. 2023 Mar 20:865:160946. doi: 10.1016/j.scitotenv.2022.160946. Epub 2022 Dec 13.

Authors

Wei Chen¹, Jianjun Zhang², Shidong Liu³, Sen Liang¹, Yaping Zhang¹, Shu Fu¹

Affiliations

¹ School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China.
² School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China; Key Laboratory of Land Consolidation and Rehabilitation, Ministry of Natural Resources, Beijing 100083, China. Electronic address: zhangjianjun@cugb.edu.cn.
³ School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China; Faculty of Science, University of Copenhagen, Copenhagen 1350, Denmark.

PMID: 36526209
DOI: 10.1016/j.scitotenv.2022.160946

Abstract

Land urbanization not only efficiently met the requirements of social development but also brought severe heating effects, especially the changes in Land Surface Temperature (LST). The effects of building density on LST and driving relation of the configuration of buildings remain poorly understood over large areas. Using Landsat 8 satellite imagery acquired from the summer of 2019, this study quantified the heating effects (k) of building density on LST across 35 cities in China, and further analyzed the driving relation of the configuration of buildings such as the size, shape, and spatial distribution on k. Here the regression analysis results showed that the building density had a significant relationship with LST, and the k varied from 1.10 to 7.27 amount of the different cities. The size and aggregation distribution of buildings were the main positive drivers for the effects of building density on LST, and the shape of buildings was not obviously related to the k-value. The results of thermal environment simulation showed that the major reason might be that the close spatial relationship reduced the heat exchange between buildings and the atmosphere, resulting in higher LST. These conclusions will provide an important reference for urban planning and design.

Keywords: Building density; Land surface temperature; Remote sensing; Spatial configuration; Urban planning.