PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai
Version 1
: Received: 20 April 2024 / Approved: 20 April 2024 / Online: 22 April 2024 (10:17:07 CEST)
How to cite:
Guan, Z.; Zhang, H. A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai. Preprints2024, 2024041367. https://doi.org/10.20944/preprints202404.1367.v1
Guan, Z.; Zhang, H. A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai. Preprints 2024, 2024041367. https://doi.org/10.20944/preprints202404.1367.v1
Guan, Z.; Zhang, H. A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai. Preprints2024, 2024041367. https://doi.org/10.20944/preprints202404.1367.v1
APA Style
Guan, Z., & Zhang, H. (2024). A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai. Preprints. https://doi.org/10.20944/preprints202404.1367.v1
Chicago/Turabian Style
Guan, Z. and Hao Zhang. 2024 "A Quantitative Analysis of the Complex Response Relationship between Urban Green Infrastructure (Ugi) Structure/Spatial Pattern and Urban Thermal Environment in Shanghai" Preprints. https://doi.org/10.20944/preprints202404.1367.v1
Abstract
The Urban heat island (UHI) effect has evolved into one of the key environmental problems affecting urban ecological environment and sustainable development. Based on 52 Urban Thermal Heat spots (UTHSs) with significant differences between land use structure and UGI spatial layout within the influence range of UHI in Shanghai, Landsat-8/9 satellite images were used to construct a high-dimensional data set reflecting the impact of built environment components on urban thermal environment. Descriptive statistical analysis was used to analyze the spatial difference qualitatively. Using stepwise regression model and partial least square regression (PLSR) model, the complex response relationship between UGI pattern differentiation and urban thermal environment in three spatial stratification ranges of UTHSs was quantitatively analyzed. Overall, the statistical explanatory power of the partial least square regression PLSR model is due to the stepwise regression model. The PLSR model points out that moderately increasing the average building height, CA, PLAND, LSI and LPI play a positive role in inhibiting/slowing down the growth of LST (land surface temperature), and the cooling effect of index weights decreases in order. However, the interaction effects of CA×Cohesion×AI×LPI and PLAND×CA×Cohesion×AI×LPI exert relatively small weight on the cooling effect, and according to the results, suggestions such as UGI structure and urban construction layout optimization can effectively alleviate the urban heat island effect are proposed.
Keywords
urban heat island effect; urban green infrastructure; land use pattern; climate adaptation
Subject
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
