GEOGRAPHICAL RESEARCH

The impact of cooling effect of micro green space in a polycentric city: Taking Hangzhou as an example

LYU Yuefeng, XIAO Yue

GEOGRAPHICAL RESEARCH, 2026, 45(4): 1155-1171. DOI: 10.11821/dlyj020250406

指标类型	指标名称	计算方法
绿地景观特征	绿地面积（S）	ArcGIS统计
	周长（C）	ArcGIS统计
	形状指数（GSI）	$GSI=\frac{L}{2\sqrt{\mathrm{\pi }\times S}}$
	植被覆盖度（NDVI）	遥感统计
城市景观特征	道路密度（RO）	ArcGIS统计与图层计算
	建筑密度（BD）	$BD=\frac{\sum _{i=1}^{n}{A}_{i}}{S}$
	建筑高度（BH）	$BH=\frac{\sum _{i=1}^{n}{H}_{i}}{S}$
	容积率（FAR）	$FAR=\frac{\sum _{i=1}^{n}({A}_{i}\times {H}_{i})}{S}$

Tab. 2 Selection of influencing factors for cooling effect

Other figure/table from this article

Tab. 1 Sorting out some characteristics of micro and small green spaces
Fig. 1 Overview of the study area (Hangzhou)
Fig. 2 The step-by-step framework
Fig. 3 Example of green patch samples
Fig. 4 Spatial distribution of green patch samples
Fig. 5 Land surface temperature change curve in the cooling process of green patches
Fig. 6 Retrieval results of Hangzhou land surface temperature
Fig. 7 The control test on the cooling effect of micro green spaces
Tab. 3 Analysis of temperature variations between green space sample group and non-green space control group
Fig. 8 Cooling characteristics of micro green spaces
Tab. 4 Correlation analysis of cooling effect and impact factors of micro green spaces
Fig. 9 Relative contribution of each influencing factor to the cooling effect of greenspace in the sub-centers
Fig. 10 Marginal effect of core factors on the cooling effect of green spaces
Fig. 11 Land use change process of Hangzhou's sub-centers (1990-2020)