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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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.

Details

Title
Modeling of Daytime and Nighttime Surface Urban Heat Island Distribution Combined with LCZ in Beijing, China
Author
Xu, Yinuo 1 ; Zhang, Chunxiao 2   VIAFID ORCID Logo  ; Hou, Wei 3   VIAFID ORCID Logo 

 School of Information Engineering, China University of Geosciences in Beijing, No. 29, Xueyuan Road, Haidian District, Beijing 100083, China 
 School of Information Engineering, China University of Geosciences in Beijing, No. 29, Xueyuan Road, Haidian District, Beijing 100083, China; Observation and Research Station of Beijing Fangshan Comprehensive Exploration, Ministry of Natural Resources, Beijing 100083, China 
 Chinese Academy of Surveying and Mapping, Lianhuachi West Road 28, Beijing 100830, China 
First page
2050
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
2073445X
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2748335596
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.