绿地景观对城市热环境的影响——以长春市建成区为例

doi:10.11821/dlyj201411009

摘要/Abstract

摘要：

绿地景观作为城市生态网络中的自然要素,在缓解城市热岛、调节城市气候中发挥着极其重要的作用。以绿地景观为研究对象,基于SPOT5影像提取长春市建成区绿地景观数据,基于TM影像估算地表温度,分析城市绿地景观与地表温度的相关关系,将“植被—不透水面—土壤”模型与具有明确物理意义的线性光谱混合模型相结合估算城市地表植被覆盖度,进一步剖析绿地景观的植被覆盖对城市热环境的影响。结果表明：绿地面积与该块绿地的最低温度负相关性较大,当绿地的面积达到50 hm²之后,面积的增大会使其地表温度显著降低;生产绿地和农业用地的地表温度最低,居住绿地地表温度最高,公园绿地温度受植被状况的影响与其他类型相比更剧烈,常绿树和落叶树的降温效果更好;增加公园绿地、常绿树和落叶树的植被覆盖,对于减缓城市热岛效应具有更好的调节作用。

关键词: 绿地景观, 植被盖度, 热环境, 定量遥感, 空间分析, 长春市

Abstract:

As the main natural productivity in urban structure, the green landscape plays an important role in mitigating the urban heat island, and regulating urban climate. In the perspective of interactive human-environment system, a case study was carried on green landscape of a typical garden city in Northeast China. SPOT5 image was selected for extraction of urban green landscape, and TM image was chosen to retrieve land surface temperature (LST). Correlation analysis was investigated between green landscape (size and area of urban green patches) and LST. The "vegetation-impervious surfaces-soil" model and the physically explicit linear spectral mixing model was combined for mapping the fractional coverage of vegetation, and the vegetation cover of green landscape on LST was further analyzed. Results showed that: (1) the area of green lands has stronger negative correlation with the lowest temperature. It was found that the LST decreased with increasing green lands when the coverage area was over 50 ha. Thus, if green land area was too small, it would have little impact on urban thermal environment; (2) the corresponding LST was low in the productive plantation area and cultivated land, and it was the highest in the residential green space. The vegetation coverage and the LST of green patches was quantitatively analyzed for the whole study area, the result revealed that the impact of vegetation growing conditions on LST of green lands in park green space was more severe than that of other green-land types. Thus, the increase of vegetation coverage in parks could be helpful for regulating the LST; (3) the LST of evergreen and deciduous forest lands was the lowest, followed by the cultivated land, while the cooling effect of grasslands was not obvious, so the LST of evergreen and deciduous forest lands was more sensitive than that of grasslands and cultivated lands, that is, the evergreen and deciduous forest lands could be helpful for alleviating the urban heat island effect.

Key words: green landscape, vegetation coverage, thermal environment, quantitative remote sensing, spatial analysis, Changchun city

王蕾, 张树文, 姚允龙. 绿地景观对城市热环境的影响——以长春市建成区为例[J]. 地理研究, 2014, 33(11): 2095-2104.

Lei WANG, Shuwen ZHANG, Yunlong YAO. The impacts of green landscape on urban thermal environment: A case study in Changchun city[J]. GEOGRAPHICAL RESEARCH, 2014, 33(11): 2095-2104.

图/表 11

图1

图2

图3

图4

图5

图6

图7

表1

图8

图9

图10

参考文献 24

[1]	Madlener R, Sunak Y.Impacts of urbanization on urban structures and energy demand: What can we learn for urban energy planning and urbanization management?.Sustainable Cities and Society, 2011, 1(1): 45-53.
[2]	Satterthwaite D.Cities' contribution to global warming: Notes on the allocation of greenhouse gas emissions. Environment and Urbanization, 2008, 20(2): 539-549.
[3]	Weng Q H.Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends. ISPRS Journal of Photogrammetry and Remote Sensing, 2009, 64(4): 335-344.
[4]	饶胜, 张惠远, 金陶陶, 等. 基于MODIS 的珠江三角洲地区区域热岛的分布特征. 地理研究, 2010, 29(1): 127-136.
	[Rao Sheng, Zhang Huiyuan, Jin Taotao, et al.The spatial character of regional heat island in Pearl River Delta using MODIS remote sensing data. Geographical Research, 2010, 29(1): 127-136.]
[5]	张浩, 马蔚纯. 基于LUCC 的城市生态安全研究进展. 生态学报, 2007, 27(5): 2109-2117.
	[Zhang Hao, Ma Weichun.Recent advances in research on LUCC: Based urban ecological security. Acta Ecologica Sinica, 2007, 27(5): 2109-2117.]
[6]	Petrosillo I, Muller F, Jones K B, et al.Use of Landscape Sciences for the Assessment of Environmental Security. New York: Springer, 2008.
[7]	Conine A, Xiang W N, Young J, et al.Planning for multi-purpose greenways in Concord, north Carolina. Landscape and Urban Planning, 2004, 68(2-3): 271-287.
[8]	Shashua-Bar L, Hoffman M E.Vegetation as a climatic component in the design of an urban street: An empirical model for predicting the cooling effect of urban green areas with trees. Energy and Buildings, 2000, 31(3): 221-235.
[9]	Hamada S, Ohta T.Seasonal variations in the cooling effect of urban green areas on surrounding urban areas. Urban Forestry&Urban Greening, 2010, 9(1): 15-24.
[10]	Zoulia I, Santamouris M, Dimoudi A.Monitoring the effect of urban green areas on the heat island in Athens. Environmental Monitoring and Assessment, 2009, 156(1-4): 275-292.
[11]	孔繁花, 尹海伟, 刘金勇, 等. 城市绿地降温效应研究进展与展望. 自然资源学报, 2013, 28(1): 171-181.
	[Kong Fanhua, Yin Haiwei, Liu Jinyong, et al.A review of research on the urban green space cooling effect. Journal of Natural Resources, 2013, 28(1): 171-181.]
[12]	陈爱莲, 孙然好, 陈利顶. 绿地格局对城市地表热环境的调节功能. 生态学报, 2013, 33(8): 2372-2378.
	[Chen Ailian, Sun Ranhao, Chen Liding.Effects of urban green pattern on urban surface thermal environment. Acta Ecologica Sinica, 2013, 33(8): 2372-2378.]
[13]	程好好, 曾辉, 汪自书, 等. 城市绿地类型及格局特征与地表温度的关系: 以深圳特区为例. 北京大学学报: 自然科学版, 2009, 45(3): 495-501.
	[Cheng Haohao, Zeng Hui, Wang Zishu, et al.Relationships between the types, pattern characteristics of urban green space and land surface temperature: A case study in Shenzhen Special Economic Zone. Acta Scientiarum Naturalium Universitatis Pekinensia, 2009, 45(3): 495-501.]
[14]	刘艳红, 郭晋平. 基于植被指数的太原市绿地景观格局及其热环境效应. 地理科学进展, 2009, 28(5): 798-804.
	[ Liu Yanhong, Guo Jinping.The research of NDVI-based urban green space landscape pattern and thermal environment. Progress in Geography, 2009, 28(5): 798-804.]
[15]	郭红, 龚文峰, 李雁, 等. 哈尔滨市热岛效应与植被的关系: 基于RS和GIS的定量研究. 自然灾害学报, 2007, 16(2): 22-26.
	[Guo Hong, Gong Wenfeng, Li Yan, et al.Relationship between heat island effect and vegetation in Harbin city: RS and GIS based quantitative study. Journal of Natural Disasters, 2007, 16(2): 22-26.]
[16]	Weng Q H, Liu H, Lu D S.Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis, United States. Urban Ecosystems, 2007, 10(2): 203-219.
[17]	Cao X, Onishi A, Chen J, et al.Quantifying the cool island intensity of urban parks using ASTER and IKONOS data. Landscape and Urban Planning, 2010, 96(4): 224-231.
[18]	钟春棋, 曾从盛, 柳铮铮. 基于谱间特征与比值型指数的水体影像识别分析. 地球信息科学, 2008, 10(5): 663-669.
	[Zhong Chunqi, Zeng Congsheng, Liu Zhengzheng.Study on terrestrial water information identified based on the analysis of spectral signature and ratio index. Geo-Information Science, 2008, 10(5): 663-669.]
[19]	陈明辉, 陈颖彪, 郭冠华, 等. 东莞市城市热环境时空变化及其驱动机制. 地理研究, 2011, 30(8): 1431-1438.
	[Chen Minghui, Chen Yingbiao, Guo Guanhuan, et al.Temporal and spatial changes of urban thermal environment and driving mechanism in Dongguan city. Geographical Research, 2011, 30(8): 1431-1438.]
[20]	Smith M O, Johnson P E, Adams J B.Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis. Journal of Geophysical Research, 1985, 90(S2): 797-804.
[21]	Adams J B, Smith M O, Gillespie A R.Imaging spectroscopy: Interpretation based on spectral mixture analysis. Remote geochemical analysis: Elemental and Mineralogical Composition, 1993, (7): 145-166.
[22]	Qin Z, Karnieli A, Berliner P.A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing, 2001, 22(18): 3719-3746.
[23]	Valor E, Caselles V.Mapping land surface emissivity from NDVI: Application to European, African, and South American Areas. Remote Sensing of Environment, 1996, 57(3): 167-184.
[24]	Jiménez-Munoz J C, Sobrino J A. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research, 2003, 108(22): 4688-4695.

绿地类型	样本数	回归函数	相关系数(P<0.01)	回归系数
公园绿地	3186	Y=-13.016X+32.129	-0.731	0.5336
附属绿地	4980	Y=-10.364X+31.991	-0.621	0.3863
居住绿地	921	Y=-9.0506X+31.552	-0.621	0.3858
生产绿地	46	Y=-8.4237X+30.595	-0.758	0.5715
防护绿地	205	Y=-14.059X+31.666	-0.672	0.4525
其他绿地	108	Y=-10.781X+31.486	-0.714	0.5095
农业用地	68	Y=-7.9748X+30.585	-0.656	0.4273