Modeling of Daytime and Nighttime Surface Urban Heat Island Distribution Combined with LCZ in Beijing, China

Yinuo Xu, Chunxiao Zhang () and Wei Hou ()
Additional contact information
Yinuo Xu: School of Information Engineering, China University of Geosciences in Beijing, No. 29, Xueyuan Road, Haidian District, Beijing 100083, China
Chunxiao Zhang: School of Information Engineering, China University of Geosciences in Beijing, No. 29, Xueyuan Road, Haidian District, Beijing 100083, China
Wei Hou: Chinese Academy of Surveying and Mapping, Lianhuachi West Road 28, Beijing 100830, China

Land, 2022, vol. 11, issue 11, 1-21

Abstract: Along with urbanization, surface urban heat island (SUHI) has attracted more attention. Due to the lack of perspective of spatial heterogeneity in relevant studies, it is difficult to propose specific strategies to alleviate the SUHI. This study discusses the impact of spatial heterogeneity on the day and night SUHI by taking one day and night in Beijing as an example, and uses it to improve the efficiency of SUHI simulation for related planning. This study, based on the local climate zone (LCZ), deeply discusses the relationship between urban morphology and the SUHI. Then, an artificial neural network (ANN) model with the LCZ is developed to predict the distribution of the SUHI. The results show that: (1) In summer, the general SUHI intensity distribution patterns are compact zone > large low-rise zone > open zone and medium floor zone > low floor zone > high floor zone. (2) Building density and albedo in dense areas are higher correlated with the SUHI than open areas. The building height has a significant negative correlation with the SUHI in high-rise zone, but has a positive correlation in middle and low floors. (3) The LCZ improves the overall accuracy of the ANN model, especially the simulation accuracy in the daytime. In terms of regions, LCZ2, LCZ8, and LCZ10 are improved to a higher degree. This study is helpful to formulate the SUHI mitigation strategies of “adapting to the conditions of the LCZ” and provide reference for improving the sustainable development of the urban thermal environment.

Keywords: surface urban heat island (SUHI); local climate zone (LCZ); artificial neural networks (ANN); urban morphology (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2073-445X/11/11/2050/pdf (application/pdf)
https://www.mdpi.com/2073-445X/11/11/2050/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jlands:v:11:y:2022:i:11:p:2050-:d:974019

Access Statistics for this article

Land is currently edited by Ms. Carol Ma

More articles in Land from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().