城市森林林木斑块特征与降温效应的关系——以北京市城区为例

doi:10.11707/j.1001-7488.20210404

摘要/Abstract

摘要：

目的: 城市绿地对城市热岛有显著的缓解作用，但是城市生态用地空间不断被挤压，可用于增加绿地的土地面积非常有限，如何通过合理的景观和群落结构配置来缓解城市热岛效应成为重中之重。本研究在更精细的影像分辨率尺度上探究林木斑块的斑块水平特征、景观配置特征以及群落组成特征对斑块降温效应的影响，以期为城市绿地的规划和管理提供依据。方法: 以北京市六环外1 km以内的城区为研究区，利用2013年9月Landsat-8 TIRS遥感影像的第10波段反演地表亮温，利用2013年8—9月0.5 m分辨率的World-view-2遥感影像提取城市森林斑块信息，基于城市森林斑块地表亮温与城区整体地表亮温的温差量化研究区域内城市森林的降温效应。然后，选取斑块面积、周长、周长面积比和形状指数4个斑块水平的景观指数，以及树冠覆盖度、平均斑块面积、斑块密度和聚集度4个景观水平的指标，探究城市森林斑块个体特征与空间配置对其降温效应的影响。同时还采取分层随机抽样法抽取398个林木斑块，进行城市森林结构抽样调查，分析城市森林群落结构与降温效应之间的关系。结果: 北京城区地表亮温平均值为29.86 ℃，不透水地表区域的地表亮温平均值为30.64 ℃，树冠覆盖面积超过1 000 m²的林木斑块地表亮温平均值为28.68 ℃，比城区低1.18 ℃，比不透水地表低1.98 ℃。在斑块水平的4个指数中，斑块面积和周长与斑块内部地表亮温最低值显著负相关（R²值分别为0.43和0.33），斑块周长面积比以及形状指数与斑块内部地表亮温的相关性较弱，且分别为正相关（R²=0.25）和负相关（R²=0.10）。在景观水平的4个指数中，作用最强的为树冠覆盖度（R²=0.312），其次为平均斑块面积（R²=0.309），二者与林木斑块的降温效应均为正相关；斑块密度与降温效应呈非线性关系，一开始地表亮温最低值随着斑块密度的增加而升高，当斑块密度的对数值达到-4.85时，地表亮温最低值随着斑块密度的增加开始下降；聚集度与降温效应呈正相关（R²=0.15）；群落结构指标与林木斑块内部地表亮温相关性整体较弱，树高与乔木株数占比与斑块内部地表亮温负相关（P < 0.05），物种多样性指数Shannon-Wiener与斑块内部地表亮温正相关（P < 0.05）。结论: 在北京，面积超过1 000 m²的林木斑块可在一定程度上缓解城市热岛效应，树冠覆盖度和斑块面积是影响林木斑块降温效应强弱的核心因素，未来城市森林建设除直接规划大尺度城市森林外，还可优先在紧靠现有绿地区域的潜在绿地区种植树木，以此来增加现有林木斑块面积，同时建议优先选择生物量较大的植物，合理进行树种配置，全力提高城市绿地降温能力。

关键词: 林木斑块, 降温能力, 城市森林, 热岛效应, 北京

Abstract:

Objective: Urban green area has significant cooling effects on urban heat island, however, urban land area for ecological uses is constantly squeezed, and land area available for increasing green land cover is usually very limited. How to mitigate urban heat island through appropriate configuration of landscapes and plant community structure has become the top priority. This study explores the influence of the patterns of forest blocks, landscape configuration and community composition on cooling effect at finer resolution scales in order to provide a basis for the urban planners and natural resource managers. Method: This paper takes the urban area within 1 km beyond the sixth Ring Road of Beijing as the research area. Land surface temperature was retrieved using the 10th band of Landsat-8 TIRS remote sensing image in September of 2013, and world-view-2 remote sensing image with 0.5 m resolution from August to September, 2013 was used to obtain vegetation information. Then, the cooling effect of urban forest was quantified by using the land surface temperature difference between forest patches and the overall urban city. Four landscape indices at patch level, including patch area, perimeter, perimeter area ratio and shape index, and four landscape indices at landscape level, including tree canopy coverage, mean patch size, patch density and aggregation index, were selected to explore the effects of individual characteristics and spatial configuration of urban forest patches on their cooling effect. At the same time, 398 forest patches were selected by stratified random sampling method to investigate their urban forest structure and analyze the relationship between urban forest community structure and cooling effect. Result: Results showed that the mean land surface temperature in Beijing urban area was 29.86 ℃, and impervious surface area was 30.64 ℃. The mean land surface temperature of tree patches over 1 000 m² was 28.68 ℃, which was 1.18 ℃ lower than that in urban area, and 1.98 ℃ lower than that in impervious surface area. Among the four landscape indices at the patch level, the patch area and perimeter were significantly negatively correlated with the minimum land surface temperature inside the forest patches(R²=0.43, 0.33), while the correlation between perimeter area ratio and shape index and the minimum land surface temperature inside the forest patch was weak, and they were positively correlated (R²=0.25) and negatively correlated (R²=0.10) respectively. There was a nonlinear relationship between patch density and their cooling effect, the minimum land surface temperature increases with the increase of patch density, but it is opposite when the logarithm of patch density reaches -4.85. The aggregation index was positively correlated with the cooling effect of forest patches(R²=0.15). The correlation between community structure index and land surface temperature was weak, the tree height and the proportion of trees in urban forest survey was negatively correlated with land surface temperature of the forest patch, and the Shannon-Wiener index was positively correlated with the land surface temperature of the forest patches(P < 0.05). Conclusion: The forest patches with an area of more than 1 000 m² in Beijing have significant cooling effects on urban heat island, and the urban tree canopy coverage and forest patch area are the key factors affecting the cooling effect of forest patches. In addition to directly planning large-scale urban forest, priority should be given to planting trees in potential areas close to the existing green areas, in order to increase the existing forest patch areas. At the same time, it is suggested that urban forest development should give priority to the selection of plants with large biomass and appropriate deployment of tree species to improve the cooling capacity of urban green space.

Key words: forest patch, cooling effect, urban forest, urban heat island, Beijing

中图分类号:

李晓婷,李彤,仇宽彪,姜莎莎,贾宝全. 城市森林林木斑块特征与降温效应的关系——以北京市城区为例[J]. 林业科学, 2021, 57(4): 32-42.

Xiaoting Li,Tong Li,Kuanbiao Qiu,Shasha Jiang,Baoquan Jia. Relationship between Patterns of Urban Forest Patches and Their Cooling Effects——A Case Study of Beijing Urban Area[J]. Scientia Silvae Sinicae, 2021, 57(4): 32-42.

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项目 Item	A/hm²	P/km	PARA	LSI
最小值 Minimum	0.10	0.18	0.01	1.03
最大值 Maximum	785.81	272.21	0.54	39.08
均值 Mean	3.22	3.42	0.16	4.81
标准差 Standard deviation	20.89	9.78	0.07	2.83

斑块类型 Patch type	A/hm²	P/km	PARA	LSI
有绝对降温效应的斑块 Absolute cooling effect	8.14	5.20	0.14	5.30
非绝对降温效应斑块 Non-absolute cooling effect	1.40	1.80	0.18	4.36

项目 Item	P	PARA	LSI	地表亮温均值 Mean value of surface temperature	地表亮温最小值 Minimum value of surface temperature	地表亮温最大值 Maximum value of surface temperature	地表亮温极差 Range value of surface temperature
A	0.923^**	-0.712^**	0.569^**	-0.363^**	-0.642^**	0.228^**	0.773^**
P		-0.387^**	0.842^**	-0.298^**	-0.571^**	0.257^**	0.738^**
PARA			0.171^**	0.327^**	0.496^**	-0.078^**	-0.504^**
LSI				-0.127^**	-0.319^**	0.229^**	0.494^**
地表亮温均值 Mean value of surface temperature					0.864^**	0.705^**	-0.161^**
地表亮温最小值 Minimum value of surface temperature						0.373^**	-0.537^**
地表亮温最大值 Maximum value of surface temperature							0.439^**

项目 Item	P_t	PD	MPS/hm²	AI
最小值 Minimum	0.03	0.48×10^-5	0.30	4.17
最大值 Maximum	0.79	2.76×10^-5	14.81	84.79
均值 Mean	0.31	1.50×10^-5	2.67	54.02
标准差 Standard deviation	0.21	0.48×10^-5	2.80	15.59

项目 Item	林分密度 Stand density/hm^-2	BA/(m²·hm^-2)	平均胸径 Mean DBH/cm	平均树高 Mean tree height/m	乔木株数占比 Percentage of arbor number	H′	J	阔叶树株数占比 Percentage of broadleaf tree number
最小值 Minimum	3	47.53	5.75	6.60	0	1.01	1.20	0
最大值 Maximum	600	141 542.82	83.60	30.00	100%	2.66	6.23	100%
均值 Mean	31	1 329.83	21.23	8.30	91%	1.19	1.20	89%
标准差 Standard deviation	37	6 686.50	8.92	3.40	15%	0.70	1.22	18%