Effects of Green Space Patterns on Urban Thermal Environment at Multiple Spatial–Temporal Scales

Yu Song, Xiaodong Song and Guofan Shao
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Yu Song: Institute of Remote Sensing and Earth Sciences, College of Science, Hangzhou Normal University, Hangzhou 311121, China
Xiaodong Song: College of Geomatics & Municipal Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
Guofan Shao: Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907, USA

Sustainability, 2020, vol. 12, issue 17, 1-18

Abstract: Land use/land cover (LULC) pattern change due to human activity is one of the key components of regional and global climate change drivers. Urban green space plays a critical role in regulating urban thermal environment, and its cooling effect has received widespread attention in urban heat island (UHI) related studies. To fully understand the effects of the landscape pattern of an urban green space in regulating the urban thermal environment, it is necessary to further study the thermal effects of the landscape pattern of the urban green space and its characteristics under varied spatial–temporal scales. In this paper, we took the urban core area of Hangzhou City as the study area and analyzed the relationships between the landscape metrics of the urban green space and land surface temperature (LST) under varied spatial scales by using correlation analysis and redundancy analysis (RDA) methods. Multi-temporal Landsat 8 thermal infrared sensor data were used to retrieve the spatial and temporal dynamics of LSTs in four consecutive seasons, and the land use classification was interpreted using SPOT (Systeme Probatoire d’Observation de la Terre) satellite imagery. The results showed that landscape dominance metrics—e.g., percentage of landscape (PLAND) and largest patch index (LPI)—were the most influential factors on urban LST. The spatial configuration of urban landscape, as represented by the fragmentation and aggregation and connectedness, also showed significant effects on LST. Furthermore, landscape pattern metrics had varied spatial scale effects on LST. Specifically, the landscape dominance metrics of urban forest showed an increased influence on LST as the spatial scale increased, while for urban water, the trend was opposite. These findings might have some practical significance for urban planning about how to spatially arrange urban green space to alleviate UHI at local and regional scales.

Keywords: urban green space; landscape pattern; land surface temperature; multiple spatial–temporal scales; redundancy analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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