城市绿地景观格局影响地表温度的通径分析——以长沙市为例

doi:10.16258/j.cnki.1674-5906.2023.01.003

生态环境学报 ›› 2023, Vol. 32 ›› Issue (1): 18-25.DOI: 10.16258/j.cnki.1674-5906.2023.01.003

城市绿地景观格局影响地表温度的通径分析——以长沙市为例

蒋恬田¹(), 杨纯¹, 廖炜², 胡力¹, 刘欢瑶³, 任勃³, 李小马¹^,^*()

1.园林生态与规划设计湖南省普通高等学校重点实验室/湖南农业大学风景园林与艺术设计学院，湖南长沙 410128
2.湖南财政经济学院工程管理学院，湖南长沙 410205
3.洞庭湖区农村生态系统健康湖南省重点实验室/湖南农业大学资源与环境学院，湖南长沙 410128

收稿日期:2022-10-13 出版日期:2023-01-18 发布日期:2023-04-06
通讯作者: *李小马（1985年生），男，副教授，博士，主要研究方向为城市生态学、城市热岛效应。E-mail: lixiaoma@hunau.edu.cn
作者简介:蒋恬田（1996年生），女，硕士研究生，主要从事城市绿地景观格局与热环境方面的研究。E-mail: JTT885@outlook.com
基金资助:
国家自然科学基金青年项目(32001161);湖南省自然科学基金面上项目(2021JJ30329)

Path Analysis of the Urban Greenspace Landscape Pattern Impacts on Land Surface Temperature: A Case Study in Changsha

JIANG Tiantian¹(), YANG Chun¹, LIAO Wei², HU Li¹, LIU Huanyao³, REN Bo³, LI Xiaoma¹^,^*()

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, P. R. China
2. College of Engineering Management, Hunan University of Finace and Economics, Changsha 410205, P. R. China
3. Hunan Provincial Key Laboratory of Rural Ecosystem Health in Dongting Lake Area/College of Resources & Environment, Hunan Agricultural University, Changsha 410128, P. R. China

Received:2022-10-13 Online:2023-01-18 Published:2023-04-06

摘要/Abstract

摘要：

优化绿地景观格局是城市绿化土地有限背景下改善城市热环境的有效途径，阐明绿地景观格局影响城市热环境的路径与机制是合理并有效地规划与管理城市绿地的基础。以长沙市为例，利用高分2号高分辨率遥感影像在乡镇（街道）尺度量化绿地面积比例和景观配置格局，基于Landsat地表温度采用通径分析方法揭示绿地景观格局影响地表温度的路径，分析其直接效应和间接效应。结果显示：（1）绿地面积比例、水体面积比例、裸地面积比例和绿地斑块密度对地表温度呈显著的直接负效应，共解释85%的地表温度变异，直接路径系数分别为-0.61、-0.54、-0.29和-0.21；（2）绿地面积比例对绿地斑块密度呈显著的直接负效应（直接路径系数-0.46），而绿地斑块密度对地表温度呈显著的直接负效应（直接路径系数-0.21），因此绿地面积比例增加间接导致地表温度升高（间接路径系数0.10），从而削弱提高绿化覆盖率以改善城市热环境的效果；（3）绿地边界密度受绿地面积比例、绿地平均斑块形状指数和绿地斑块密度显著影响，但其对地表温度的影响不显著。因此，以小面积斑块为主的见缝插绿式绿地建设是长沙城市绿地规划管理以改善城市热环境的有效措施。

关键词: 城市热环境, 地表温度, 景观配置, 城市绿地, 通径分析

Abstract:

Optimizing the landscape pattern of urban greenspace has been widely acknowledged as an effective strategy to improve the urban thermal environment (UTE), especially when land is very limited for greening in urban areas. The landscape pattern of urban greenspace includes two aspects: landscape component (i.e., percent green cover) and landscape configuration (e.g., patch density, edge density, and patch shape). The significant negative relationships between percent green cover and urban thermal environment usually measured by air temperature (AT) and land surface temperature (LST) are consistently reported in the literature, but the relationships between landscape configuration of urban greenspace and UTE varied among studies in terms of significance, direction, and magnitude. There are strong correlations between percent green cover and landscape configuration of urban greenspace, which may impact the observed impacts of landscape pattern of urban greenspace on UTE. For example, the increase in percent green cover may decrease the patch density of urban greenspace. Therefore, the percent green cover may, directly and indirectly, impact AT or LST. Uncovering the paths of the impact of urban greenspace landscape patterns on UTE can help better understand the mechanism of the impact of urban greenspace landscape patterns on UTE and design more cost-effective urban planning and management policies. Taking Changsha as a case study, we measured the landscape pattern of urban greenspace by the commonly used landscape metrics (i.e., percent green cover, percent water cover, percent bare land cover, patch density of greenspace, edge density of greenspace, and mean patch shape index of greenspace) for 69 census tracts (administrative units at the town level) based on the proportion of green coverage and landscape configuration pattern at the township scale from the Gaofen-2 satellite high-resolution remote sensing images taken on 3rd November 2019. Mean LST for each census tract was quantified based on the LST data obtained from Landsat-8 on a clear sky day on17th August 2019. We developed direct and indirect theoretical paths to model the impact of the landscape pattern of urban greenspace on LST using the path analysis method. Results showed that (1) percent green cover, percent water cover, percent bare land and patch density of urban greenspace showed significant direct impacts on LST with the path coefficients of -0.61, -0.54, -0.29, and -0.21, respectively, and together explained 85% of the variance of LST. (2) Increasing percent green cover indirectly increased LST with a path coefficient of 0.1 through the path of decreasing patch density of urban greenspace, which weakened the cooling effect of increasing percent green cover. (3) Edge density of urban greenspace was significantly impacted by percent tree cover, mean patch shape, and patch density of urban greenspace, but it did not significantly impact LST. Our study suggests the strategy of “planting tree wherever possible” in the form of small green patches can effectively improve the UTE in Changsha.

Key words: urban thermal environment, land surface temperature, landscape configuration, urban greenspace, path analysis

中图分类号:

Q948
X16

蒋恬田, 杨纯, 廖炜, 胡力, 刘欢瑶, 任勃, 李小马. 城市绿地景观格局影响地表温度的通径分析——以长沙市为例[J]. 生态环境学报, 2023, 32(1): 18-25.

JIANG Tiantian, YANG Chun, LIAO Wei, HU Li, LIU Huanyao, REN Bo, LI Xiaoma. Path Analysis of the Urban Greenspace Landscape Pattern Impacts on Land Surface Temperature: A Case Study in Changsha[J]. Ecology and Environment, 2023, 32(1): 18-25.

图/表 4

图1 地表温度及土地覆盖图

Figure 1 Land surface temperature map and Land cover map

表1 景观格局指数描述与公式

Table 1 Description and equations of the selected landscape metrics

景观格局指数	缩写	描述（单位）	公式
绿地面积比例	P_g	绿地总面积占分析单元的百分比 (%)	$100 A × ∑ g = 1 n a g$
不透水面面积比例	P_i	不透水面总面积占分析单元的百分比 (%)	$100 A × ∑ i = 1 n a i$
水体面积比例	P_w	水体总面积占分析单元的百分比 (%)	$100 A × ∑ w = 1 n a w$
裸地面积比例	P_b	裸地总面积占分析单元的百分比 (%)	$100 A × ∑ b = 1 n a b$
绿地斑块密度	PD_g	绿地斑块数除以分析单元面积, 其值越大, 绿地斑块越破碎 (ind·km^-2)	$n A × 106$
绿地边界密度	ED_g	每公顷绿地所有边缘部分的总长度 (不包括边界), 反映绿地的破碎程度 (m·hm^-2)	$10000 A × ∑ g = 1 n e g$
平均绿地斑块形状指数	SI_g	形状指数的平均值	$1 n × ∑ g = 1 n e g min e g$

表1 景观格局指数描述与公式

Table 1 Description and equations of the selected landscape metrics

景观格局指数	缩写	描述（单位）	公式
绿地面积比例	P_g	绿地总面积占分析单元的百分比 (%)	$100 A × ∑ g = 1 n a g$
不透水面面积比例	P_i	不透水面总面积占分析单元的百分比 (%)	$100 A × ∑ i = 1 n a i$
水体面积比例	P_w	水体总面积占分析单元的百分比 (%)	$100 A × ∑ w = 1 n a w$
裸地面积比例	P_b	裸地总面积占分析单元的百分比 (%)	$100 A × ∑ b = 1 n a b$
绿地斑块密度	PD_g	绿地斑块数除以分析单元面积, 其值越大, 绿地斑块越破碎 (ind·km^-2)	$n A × 106$
绿地边界密度	ED_g	每公顷绿地所有边缘部分的总长度 (不包括边界), 反映绿地的破碎程度 (m·hm^-2)	$10000 A × ∑ g = 1 n e g$
平均绿地斑块形状指数	SI_g	形状指数的平均值	$1 n × ∑ g = 1 n e g min e g$

图2 绿地景观格局影响地表温度的路径理论路径模型（a）；基于多模型推断的路径模型（b）；优化路径模型（c）（“→”代表直接影响路径，虚箭头代表正效应，实箭头代表负效应，宽度代表路径系数绝对值。***P≤0.001；0.001<**P≤0.01；*0.01<P≤0.05。Pg，绿地面积比例；SIg，平均绿地斑块形状指数；EDg，绿地边界密度；PDg，绿地斑块密度；LST，地表温度；Pw，水体面积比例；Pb，裸地面积比例）

Figure 2 The path diagrams of Green Space Landscape pattern affecting Land Surface temperature

表2 描述性统计分析

Table 2 Descriptive statistics of LST and landscape metrics

景观格局指数	最小值	最大值	平均值	标准差
地表温度/℃	42.98	50.98	46.87	1.69
绿地面积比例P_g/%	14.95	57.65	38.57	10.24
不透水面积比例P_i/%	34.68	85.00	55.06	12.89
水体面积比例P_w/%	0.00	21.85	3.40	4.49
裸地面积比例P_b/%	0.00	16.59	2.97	3.29
绿地斑块密度PD_g/(ind·km^-2)	205.47	954.95	454.83	154.18
绿地边界密度ED_g/(m·hm^-2)	418.51	896.23	628.74	115.30
平均绿地斑块形状指数SI_g	1.35	1.60	1.48	0.06

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城市绿地景观格局影响地表温度的通径分析——以长沙市为例

Path Analysis of the Urban Greenspace Landscape Pattern Impacts on Land Surface Temperature: A Case Study in Changsha

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