Assessing the Contributions of Urban Green Space Indices and Spatial Structure in Mitigating Urban Thermal Environment

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-05, Vol.15 (9), p.2414
• Main Authors: Zhang, Yu, Wang, Yuchen, Ding, Nan, Yang, Xiaoyan
• Format: Article
• Language: English
• Subjects: Agglomeration; Ambient temperature; Analysis; Bivariate analysis; Cohesion; contribution weight; Cooling; Cooling effects; Density; Earth resources technology satellites; Energy consumption; Evaluation; Evapotranspiration; Green infrastructure; Heat; Influence coefficient; Land surface temperature; Landsat; Landsat 8; Landscape; landscape pattern; Open spaces; Principal components analysis; Radiation; Regional planning; Regression analysis; Regression coefficients; Remote sensing; Spatial analysis; Temperature; thermal environment; Thermal environments; Urban areas; Urban climatology; urban green space; Urban heat islands; Urban planning; Urbanization; Vegetation; Vegetation index
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15092414

Urban green space takes a dominant role in alleviating the urban heat island (UHI) effect. Most investigations into the effects of cooling factors from urban green spaces on the UHI have evaluated the correlation between each factor and land surface temperature (LST) separately, and the contribution weights of various typical cooling factors in mitigating the thermal environment have rarely been analyzed. For this research, three periods of Landsat 8 data captured between 2014 and 2018 of Xuzhou during the summer and autumn seasons were selected along with corresponding meteorological and flux measurements. The mono-window method was employed to retrieve LST. Based on the characteristics of the vegetation and spatial features of the green space, eight factors related to green space were selected and computed, consisting of three indices that measure vegetation and five metrics that evaluate landscape patterns: vegetation density (VD), evapotranspiration (ET), green space shading degree (GSSD), patch area ratio (PLAND), largest patch index (LPI), patch natural connectivity (COHESION), patch aggregation (AI), and patch mean shape index distribution (SHPAE_MN). Linear regression and bivariate spatial autocorrelation analyses between each green space factor and LST showed that there were significant negative linear and spatial correlations between all factors and LST, which proved that the eight factors were all cooling factors. In addition, LST was strongly correlated with all factors (|r| > 0.5) except for SHPAE_MN, which was moderately correlated (0.3 < |r| < 0.5). Based on this, two principal components were extracted by applying principal component analysis with all standardized green space factors as the original variables. To determine the contribution weight of each green space factor in mitigating the urban heat island (UHI) effect, we multiplied the influence coefficient matrix of the initial variables with the standardized multiple linear regression coefficients between the two principal component variables and LST. The final results indicated that the vegetation indices of green space contribute more to the alleviation of the UHI than its landscape pattern metrics, and the contribution weights are ranked as VD ≥ ET > GSSD > PLAND ≈ LPI > COHESION > AI > SHAPE_MN. Our study suggests that increasing vegetation density is preferred in urban planning to mitigate urban thermal environment, and increasing broadleaf forests with high evapotranspiration an