Spatial Configuration of Urban Greenspace Affects Summer Air Temperature: Diurnal Variations and Scale Effects
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Published:2023-09-14
Issue:9
Volume:14
Page:1433
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ISSN:2073-4433
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Container-title:Atmosphere
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language:en
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Short-container-title:Atmosphere
Author:
Tian Qin1, Qiu Qingdong2, Wang Zhiyu2, Cai Zhengwu3, Hu Li1, Liu Huanyao4, Feng Ye1, Li Xiaoma1
Affiliation:
1. Hunan Provincial Key Laboratory of Landscape Ecology and Planning & Design in Regular Higher Educational Institutions, College of Landscape Architecture and Art Design, Hunan Agricultural University, Changsha 410128, China 2. Changsha Meteorological Bureau, Changsha 410205, China 3. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China 4. Hunan Provincial Key Laboratory of Rural Ecosystem Health in Dongting Lake Area, College of Environment and Ecology, Hunan Agricultural University, Changsha 410128, China
Abstract
Optimizing the spatial pattern (spatial compositive and spatial configuration) of urban greenspace can effectively alleviate the urban heat island effect. While the relationship between air temperature (AT) and spatial composition of urban greenspace has been widely studied, this study aimed to investigate the relationship between AT and spatial configuration of urban greenspace and its diurnal variations and scale effects. Based on hourly AT data from 36 meteorological stations in Changsha, China, and land cover data interpreted from the Gaofen 2 remote sensing images, this study first quantified spatial composition (i.e., percent of greenspace) and spatial configuration (i.e., average patch area, patch density, edge density, landscape shape index, and mean shape index) of urban greenspace at different scales (30 m to 2000 m buffer surrounding the air station), then Pearson correlations (between AT and each landscape metric) and partial Pearson correlations (between AT and spatial configuration metrics with percent of greenspace controlled) were analyzed. Multiple linear regression was applied to model the variation of AT using the landscape metrics as independent variables. Finally, the variance partitioning analysis was performed to investigate the relative importance of spatial composition and spatial configuration of urban greenspace to explain the variation of AT. The results showed that (1) the temperature range reached 1.73 °C during the day and 2.94 °C at night. Urban greenspace was fragmented especially at small scales. (2) The Pearson correlation between AT and percent of greenspace fluctuated with the increase of scale and was generally higher during the day than during the night. (3) The spatial pattern of urban greenspace explained as high as 55% of the AT variation, showing diurnal variations and scale effects (i.e., a maximum of 0.54 during the day at 50 m buffer and a maximum of 0.55 during the night at 400 m buffer). (4) A higher percent of greenspace, more aggregated greenspace patches, and simpler greenspace shapes can generate a stronger cooling effect. (5) The relative importance of spatial composition and spatial configuration of greenspace varied among spatial scales and showed diurnal variations. These results emphasize the scale effect as well as diurnal variation of the relationship between urban greenspace spatial pattern and AT. These findings provide theoretical guidance for urban greenspace planning and management to improve the urban thermal environment in rapidly developing subtropical cities such as Changsha, China.
Funder
National Natural Science Foundation of China Hunan Provincial Natural Science Foundation of China
Subject
Atmospheric Science,Environmental Science (miscellaneous)
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