高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

城市居住区绿地小微尺度下垫面构成对环境微气候的影响

范舒欣 李坤 张梦园 谢雅芬 董丽

范舒欣, 李坤, 张梦园, 谢雅芬, 董丽. 城市居住区绿地小微尺度下垫面构成对环境微气候的影响——以北京地区为例[J]. 北京林业大学学报. doi: 10.12171/j.1000-1522.20200256
引用本文: 范舒欣, 李坤, 张梦园, 谢雅芬, 董丽. 城市居住区绿地小微尺度下垫面构成对环境微气候的影响——以北京地区为例[J]. 北京林业大学学报. doi: 10.12171/j.1000-1522.20200256
Fan Shuxin, Li Kun, Zhang Mengyuan, Xie Yafen, Dong Li. Effects of micro scale land-cover type and pattern of urban residential area on microclimate:Take Beijing as a case study[J]. Journal of Beijing Forestry University. doi: 10.12171/j.1000-1522.20200256
Citation: Fan Shuxin, Li Kun, Zhang Mengyuan, Xie Yafen, Dong Li. Effects of micro scale land-cover type and pattern of urban residential area on microclimate:Take Beijing as a case study[J]. Journal of Beijing Forestry University. doi: 10.12171/j.1000-1522.20200256

城市居住区绿地小微尺度下垫面构成对环境微气候的影响

——以北京地区为例

doi: 10.12171/j.1000-1522.20200256
基金项目: 北京林业大学科技创新计划项目(BLX201811),中国博士后科学基金项目(2018M641221),北京市科技计划项目(D171100007117001),北京林业大学建设世界一流学科和特色发展引导专项(风景园林学)(2019XKJS0320)
详细信息
    作者简介:

    范舒欣,博士,讲师。主要研究方向:城市绿地生态系统服务、园林植物应用与园林生态、植物景观规划设计。Email:fanshuxin_09@bjfu.edu.cn 地址:100083 北京市海淀区清华东路35号北京林业大学园林学院

    责任作者:

    董丽,教授,博士生导师。主要研究方向:园林植物应用、植物景观规划设计、园林生态效益及生态修复。电话:13911560585 Email :dongli@bjfu.edu.cn 地址:同上

Effects of micro scale land-cover type and pattern of urban residential area on microclimate:Take Beijing as a case study

  • 摘要:   目的  城市人居环境中小微尺度是人们日常使用最频繁的基本空间尺度。探究小微尺度下垫面类型及其格局特征对环境微气候的影响机制,是借助风景园林规划设计策略改善城市热环境的理论基础。  方法  本研究基于实地测量,针对城市居住区绿地不同类型下垫面日均空气温度、湿度的差异,以及小微尺度下垫面格局对环境微气候的影响开展定量研究。  结果  四季7种下垫面类型的日均温度、湿度均存在显著差异,且7种下垫面类型的排序有季节性变化。高郁闭度植被、水体与中郁闭度植被的降温、增湿效应明显。借助景观格局指数量化不同类型下垫面的格局特征。景观指数与日均温度、湿度的相关性随不同季节而变化。各类下垫面的面积占比、斑块面积是影响小微尺度环境温度、湿度的关键格局特征,破碎度与聚集度也有一定影响。  结论  未来进行热舒适型小微尺度户外空间节点设计时,提高高郁闭度与中郁闭度植被的面积占比和斑块面积,控制其破碎程度,采用聚集式布局形式可有效提高环境相对湿度,降低空气温度。同时应避免配置成片的硬质铺装(占比率高,面积大,分布聚集),降低其热调节负效应。

     

  • 图  1  21个下垫面类型样方和7个复合样方的位置分布示意图

    图像来源:2014年9月谷歌地图Picture source: Google Maps, September 2014 Site A ~ G:样方A ~ G;HVC1 ~ 3:高郁闭度植被垫面1 ~ 3;MVC1 ~ 3:中郁闭度植被垫面1 ~ 3;LVC1 ~ 3:低郁闭度植被垫面1 ~ 3;WB1 ~ 3:水体垫面样点1 ~ 3;BS1 ~ 3:裸土垫面样点1 ~ 3;BA1 ~ 3:建筑垫面样点1 ~ 3;PA1 ~ 3:不透水铺装垫面样点。下同。Site A ~ G: Quadrat A-G; HVC1 ~ 3: High canopy density vegetation 1-3; MVC1 ~ 3: Moderate canopy density vegetation 1-3; LVC1 ~ 3: Low canopy density vegetation 1-3; WB1 ~ 3: Water-Body 1-3; BS1 ~ 3: Bare Soil 1-3; BA1 ~ 3: Building Area 1-3; PA1 ~ 3: Paved Area 1-3. The same below.

    Figure  1.  Locations of study areas, 21 type sites, and 7 pattern sites

    图  2  格局试验复合样方范围内测点示例(样方E、G)

    Figure  2.  Arrangement example of three measuring points for pattern site (Site E and G)

    图  3  四季7种下垫面类型的日平均空气温度

    不同小写字母表示多重比较的差异。下同。Different lowercase letters indicate the differences of multiple comparisons. The same below.

    Figure  3.  Daily average air temperature among seven land-cover types in the four seasons

    图  4  四季7种下垫面类型的日平均相对湿度

    Figure  4.  Daily average relative humidity among seven land-cover types in the four seasons.

    图  5  四季不同下垫面格局样方的日平均空气温度、湿度分布

    Figure  5.  Distribution of daily average AT and RH at seven pattern sites in four seasons

    表  1  3类植被垫面的基本信息

    Table  1.   Details of the sampling vegetation underlying surface

    群落编号
    No.
    群落类型
    Community type
    郁闭度
    Canopy density/%
    平均株高
    Average Height/m
    平均冠幅
    Average crown diameter/m
    平均胸径(地径)
    Average DBH (GD)/cm
    HVC1 针阔混交−乔灌草型
    Mixed coniferous and broad-leaved trees,
    shrubs and grasses (M-TSG)
    89 6.21 4.30 11.25
    HVC2 针阔混交−乔灌草型 (M-TSG) 83 6.93 2.22 15.35
    HVC3 针阔混交−乔灌草型 (M-TSG) 92 4.79 3.91 8.73
    MVC1 阔叶−乔灌草型
    Broad-leaved trees, shrubs and grasses (B-TSG)
    61 5.40 3.95 16.00
    MVC2 针阔混交−乔灌草型 (M-TSG) 48 8.84 3.26 10.18
    MVC3 针阔混交−乔草型
    Mixed coniferous and broad-leaved
    trees and grasses (M-TG)
    53 9.29 4.46 14.53
    LVC1 针阔混交−乔灌草型 (M-TSG) 38 5.32 1.66 7.23
    LVC2 针阔混交−乔草型 (M-TG) 19 3.98 4.08 7.60
    LVC3 针阔混交−乔灌草型 (M-TSG) 32 8.84 3.26 8.18
    下载: 导出CSV

    表  2  所选景观指数

    Table  2.   List of selected landscape metrics

    景观指数 Metrics水平 Level描述 Description单位 Unit范围 Range
    斑块所占景观面积比例
    Percent of landscape (PLAND)
    类型 Type 某一斑块类型占景观的面积比率
    The area ratio of a certain patch type to the landscape
    % 0 ~ 100
    斑块密度
    Patch density (PD)
    每公顷某一斑块类型斑块的个数
    The number of a certain patch type per hectare
    个/hm2
    Number/ha
    > 0
    平均斑块面积
    Mean patch size (MPS)
    某一斑块类型的平均斑块面积
    Mean patch size of a certain patch type
    hm2
    ha
    > 0
    破碎度指数
    Fragmentation index (FI)
    某一斑块类型被分割的破碎程度
    The degree of fragmentation of a certain patch type
    / > 0
    聚集度指数
    Aggregation index (AI)
    某一斑块类型相互聚集的程度
    The degree of aggregation of a certain patch type
    % 0 ~ 100
    下载: 导出CSV

    表  3  所选格局样方的景观指数信息

    Table  3.   Landscape metrics of the seven pattern sites

    景观指数
    Landscape index
    样方编号 Site No.
    Site ASite BSite CSite DSite ESite FSite G
    PA PLAND 50.130 33.523 33.334 58.203 31.113 25.268 50.814
    PD 5.391 5.375 4.030 2.695 2.687 2.696 2.694
    MPS 0.093 0.062 0.083 0.216 0.116 0.094 0.189
    FI 32.258 48.077 24.184 4.630 8.636 10.672 5.302
    AI 97.391 95.903 97.281 98.456 96.532 96.076 98.500
    BA PLAND 24.661 22.902 48.178 26.951 20.857 18.920 33.127
    PD 2.696 4.031 4.030 5.390 8.060 6.739 5.389
    MPS 0.092 0.057 0.120 0.050 0.026 0.028 0.062
    FI 10.929 35.211 16.722 60.000 193.050 142.349 48.780
    AI 99.099 98.592 98.263 97.892 97.103 97.487 97.700
    LVC PLAND 3.101 20.618 15.427 9.468 24.448 30.602 10.278
    PD 2.696 10.749 13.433 12.128 13.433 9.434 10.778
    MPS 0.012 0.019 0.012 0.008 0.018 0.032 0.010
    FI 86.957 364.583 782.609 1025.641 494.505 185.185 736.842
    AI 97.909 95.606 93.370 93.152 95.612 96.290 94.260
    MVC PLAND 20.903 8.247 2.005 1.919 13.952 17.551 3.700
    PD 8.087 4.031 2.687 2.695 9.403 8.087 4.042
    MPS 0.026 0.021 0.008 0.007 0.015 0.022 0.009
    FI 193.798 97.561 133.333 140.845 405.405 230.415 217.391
    AI 97.075 97.003 95.497 94.404 94.949 96.280 96.133
    HVC PLAND 1.205 14.710 1.056 3.459 9.631 7.660 2.080
    PD 1.348 2.687 1.343 2.695 4.030 2.696 2.694
    MPS 0.009 0.055 0.008 0.013 0.024 0.028 0.008
    FI 0.000 18.282 0.000 78.125 83.682 35.211 129.870
    AI 99.085 98.132 96.856 98.218 97.184
    注:HVC:高郁闭度植被垫面;MVC:中郁闭度植被垫面;LVC:低郁闭度植被垫面;BA:建筑垫面样点;PA:不透水铺装垫面样点。下同。Notes: HVC: High canopy density vegetation;MVC: Moderate canopy density vegetation; LVC: Low canopy density vegetation; BA: Building Area;PA: Paved Area.
    下载: 导出CSV

    表  4  四季各景观指数与日平均空气温度与相对湿度的相关性

    Table  4.   Spearman correlations between landscape metrics and daily average AT and RH in four seasons

    景观指数
    Landscape index
    日均空气温度 daily average AT/℃日均相对湿度 daily average RH/%
    冬季 WIN.春季 SPR.夏季 SUM.秋季 AUT.冬季 WIN.春季 SPR.夏季 SUM.秋季 AUT.
    PA PLAND 0.852* 0.895** 0.761* 0.808* −0.844* −0.794* −0.823* −0.809*
    PD 0.089 0.093 −0.245 −0.158 0.076 0.175 0.055 −0.045
    MPS 0.616 0.639 0.740 0.736 −0.703 −0.735 −0.675 −0.619
    FI −0.040 −0.060 −0.379 −0.281 0.219 0.292 0.193 0.067
    AI 0.784* 0.842* 0.933** 0.898** −0.908** 0.897** −0.888** −0.825*
    BA PLAND 0.362 0.445 0.647 0.564 −0.572 −0.583 0.610 −0.56
    PD −0.561 −0.547 −0.236 −0.271 0.427 0.343 0.413 0.484
    MPS 0.382 0.453 0.422 0.380 −0.462 −0.408 −0.491 −0.473
    FI −0.745 −0.730 −0.489 −0.510 0.655 0.596 0.637 0.708
    AI 0.421 0.411 0.041 0.105 −0.25 −0.154 −0.245 −0.322
    LVC PLAND −0.759* −0.833* −0.692 −0.72 0.773* 0.684 0.771* 0.759*
    PD −0.143 −0.065 0.242 0.245 −0.081 −0.174 −0.149 −0.106
    MPS −0.709 −0.854* −0.875** −0.917** 0.860* 0.801* 0.907** 0.868
    FI 0.536 0.633 0.820* 0.830* −0.745 −0.800* −0.788* −0.724*
    AI −0.443 −0.507 −0.711 −0.701 0.637 0.715 0.675 0.629
    MVC PLAND −0.579 −0.631* −0.767* −0.780* 0.729 0.783* 0.760* 0.763*
    PD −0.758* −0.758* −0.705 −0.733 0.785* 0.818* 0.791* 0.835*
    MPS −0.413 −0.511 −0.799* −0.767* 0.669 0.734 0.712 0.635
    FI −0.681 −0.598 −0.278 −0.325 0.507 0.504 0.476 0.574
    AI −0.035 0.174 −0.429 −0.433 0.291 0.357 0.359 0.211
    HVC PLAND −0.485 −0.536 −0.658 −0.539 0.624 0.605 0.599 0.488
    PD −0.429 −0.408 −0.228 −0.174 0.367 0.320 0.342 0.345
    MPS −0.352 −0.439 −0.656 −0.536 0.556 0.543 0.548 0.407
    FI 0.214 0.216 0.473 0.451 −0.326 −0.367 −0.298 −0.287
    AI −0.120 −0.119 −0.519 −0.409 0.314 0.364 0.296 0.302
    注:粗体为显著变量,**表示极显著相关(P < 0.01),*表示显著相关(P < 0.05)。Note: Significant variables are marked in bold, ** stands for significant P value < 0.01, showing a very significant correlation; * stands for significant P value < 0.05, showing a significant correlation.
    下载: 导出CSV
  • [1] Gao Z, Hou Y, Chen W. Enhanced sensitivity of the urban heat island effect to summer temperatures induced by urban expansion[J]. Environmental Research Letters, 2019, 14(9): 094005. doi: 10.1088/1748-9326/ab2740
    [2] Peng J, Ma J, Liu Q, et al. Spatial-temporal change of land surface temperatureIcross 285 cities In China: An urban-rural contrast perspective[J]. Science of The Total Environment, 2018, 635: 487−497. doi: 10.1016/j.scitotenv.2018.04.105
    [3] Rizwan A M, Dennis L Y C, Liu C H. A review on the generation, determination and mitigation of Urban Heat Island[J]. Journal of Environmental Science, 2008, 20(1): 120−128. doi: 10.1016/S1001-0742(08)60019-4
    [4] Gosling S N, Lowe J A, Mcgregor G R, et al. Associations between elevated atmospheric temperature and human mortality: a critical review of the literature[J]. Climatic Change, 2009, 92(3-4): 299−341. doi: 10.1007/s10584-008-9441-x
    [5] 潘守文. 小气候考察的理论基础及其应用[M]. 北京: 气象出版社, 1989.

    Pan S W. Theoretical basis and application of microclimate investigation[M]. Beijing: China Meteorological Press, 1989.
    [6] Algretawee H, Rayburg S, Neave M. Estimating the effect of park proximity to the central of Melbourne city on Urban Heat Island (UHI) relative to Land Surface Temperature (LST)[J]. Ecological Engineering, 2019, 138: 374−390. doi: 10.1016/j.ecoleng.2019.07.034
    [7] Zenghui K, Zhibao W, Xuejun S, et al. Research on the cooling island effects of water body: A case study of Shanghai, China[J]. Ecological indicators: Integrating, monitoring, assessment and management, 2016, 67: 31−38.
    [8] Du H, Cai W, Xu Y, et al. Quantifying the cool island effects of urban green spaces using remote sensing Data[J]. Urban Forestry & Urban Greening, 2017, 27: 24−31.
    [9] 谢紫霞, 张彪, 佘欣璐, 等. 上海城市绿地夏季降温效应及其影响因素[J]. 生态学报, 2020, 40(19):6749−6760.

    Xie Z X, Zhang B, She X L, et al. The summer cooling effect and its influencing factors of urban green spaces in Shanghai[J]. Acta Ecologica Sinica, 2020, 40(19): 6749−6760.
    [10] Liu F, Zhang X, Murayama Y, et al. Impacts of land cover/use on the urban thermal environment: A comparative study of 10 megacities in China[J/OL]. Remote Sensing, 2020, 12(2): 307 [2020−03−02]. https://doi.org/10.3390/rs12020307.
    [11] Fan S, Li X, Han J, et al. Assessing the effects of landscape characteristics on the thermal environment of open spaces in residential areas of Beijing, China[J]. Landscape & Ecological Engineering, 2018, 14: 79−90.
    [12] 仇宽彪, 贾宝全, 成军锋. 北京市五环内主要公园冷岛效应及其主要影响因素[J]. 生态学杂志, 2017, 36(7):1984−1992.

    Qiu K, Jia B, Cheng J. Cool island effect of urban parks and its influencing factors within the Fifth Ring in Beijing[J]. Chinese Journal of Ecology, 2017, 36(7): 1984−1992.
    [13] Gage E A, Cooper D J. Relationships between landscape pattern metrics, vertical structure and surface urban Heat Island formation in a Colorado suburb[J]. Urban Ecosystems, 2017, 20(6): 1229−1238. doi: 10.1007/s11252-017-0675-0
    [14] 陈爱莲, 孙然好, 陈利顶. 传统景观格局指数在城市热岛效应评价中的适用性[J]. 应用生态学报, 2012, 23(8):2077−2086.

    Chen A L, Sun R H, Chen L D. Applicability of traditional landscape metrics in evaluating urban heat island effect[J]. Chinese Journal of Applied Ecology, 2012, 23(8): 2077−2086.
    [15] Chen A, Yao L, Sun R, et al. How many metrics are required to identify the effects of the landscape pattern on land surface temperature?[J]. Ecological Indicators, 2014, 45(1): 424−433.
    [16] 邹婧, 曾辉. 城市地表热环境与景观格局的关系: 以深圳市为例[J]. 北京大学学报: 自然科学版, 2017, 53(3):436−444.

    Zou J, Zeng H. Relationships between urban landscape pattern and land surface temperature: A case study of Shenzhen[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2017, 53(3): 436−444.
    [17] 花利忠, 孙凤琴, 陈娇娜, 等. 基于Landsat-8影像的沿海城市公园冷岛效应: 以厦门为例[J]. 生态学报, 2020, 40(22):1−11.

    Hua L Z, Sun F Q, Chen J N, et al. Quantifying the cool-island effects of urban parks using Landsat-8 imagery in a coastal city, Xiamen, China[J]. Acta ecologica Sinica, 2020, 40(22): 1−11.
    [18] Hai Y, Fan W, Li D. Influence of a large urban park on the local urban thermal environment[J]. Science of the Total Environment, 2018, 622-623(May1): 882−891.
    [19] Zhao J, Zhao X, Liang S, et al. Assessing the thermal contributions of urban land cover types[J]. Landscape and Urban Planning, 2020, 204: 103927. doi: 10.1016/j.landurbplan.2020.103927
    [20] Wu Z, Chen L. Optimizing the spatial arrangement of trees in residential neighborhoods for better cooling effects: Integrating modeling with in-situ measurements[J]. Landscape and Urban Planning, 2017, 167: 463−472. doi: 10.1016/j.landurbplan.2017.07.015
    [21] Coseo P, Larsen L. How factors of land use/land cover, building configuration, and adjacent heat sources and sinks explain Urban Heat Islands in Chicago[J]. Landscape & Urban Planning, 2014, 125: 117−129.
    [22] Sun R, Chen L. Effects of green space dynamics on urban heat islands: Mitigation and diversification[J]. Ecosystem Services, 2017, 23: 38−46. doi: 10.1016/j.ecoser.2016.11.011
    [23] Skelhorn C, Lindley S, Levermore G. The impact of vegetation types on air and surface temperatures in a temperate city: A fine scale assessment in Manchester, UK[J]. Landscape & Urban Planning, 2014, 121: 129−140.
    [24] 朱春阳, 李树华, 纪鹏. 城市带状绿地结构类型与温湿效应的关系[J]. 应用生态学报, 2011, 22(5):1255−1260.

    Zhu C Y, Li S H, Ji P. Relationships between urban green belt structure and temperature-humidity effect[J]. Chinese Journal of Applied Ecology, 2011, 22(5): 1255−1260.
    [25] Srivanit M, Hokao K. Evaluating the cooling effects of greening for improving the outdoor thermal environment at an institutional campus in the summer[J]. Building and Environment, 2013, 66(Supplement C): 158−172.
    [26] Skelhorn C, Lindley S, Levermore G. The impact of vegetation types on air and surface temperatures in a temperate city: A fine scale assessment in Manchester, UK[J]. Landscape & Urban Planning, 2014, 121(1): 129−140.
    [27] 高吉喜, 宋婷, 张彪, 等. 北京城市绿地群落结构对降温增湿功能的影响[J]. 资源科学, 2016, 38(6):1028−1038.

    Gao J X, Song T, Zhang B, et al. The relationship between urban green space community structure and air temperature reduction and humidity increase in Beijing[J]. Resources Science, 2016, 38(6): 1028−1038.
    [28] Lin T, Ho Y, Huang Y. Seasonal effect of pavement on outdoor thermal environments in subtropical Taiwan[J]. Building and Environment, 2007, 42(12): 4124−4131. doi: 10.1016/j.buildenv.2006.11.031
    [29] 刘娇妹, 杨志峰. 北京市冬季不同景观下垫面温湿度变化特征[J]. 生态学报, 2009, 29(6):3241−3252. doi: 10.3321/j.issn:1000-0933.2009.06.056

    Liu J M, Yang Z F. Dynamicss of temperature and humidity in underlaying surface of different landscape type in winter in Beijing City, China[J]. Acta Ecologica Sinica, 2009, 29(6): 3241−3252. doi: 10.3321/j.issn:1000-0933.2009.06.056
    [30] Dimoudi A, Nikolopoulou M. Vegetation in the urban environment: microclimatic analysis and benefits[J]. Energy & Buildings, 2003, 35(1): 69−76.
    [31] Bartesaghi, Koc, Carlos, et al. Evaluating the cooling effects of green infrastructure: A systematic review of methods, indicators and data sources[J]. Solar Energy Phoenix Arizona Then New York, 2018.
    [32] 邹春城, 张友水, 黄欢欢. 福州市城市不透水面景观指数与城市热环境关系分析[J]. 地球信息科学学报, 2014, 16(3):490−498.

    Zou C C, Zhang Y S, Huang H H. Impacts of Impervious Surface Area and Landscape Metrics on Urban Heat Environment in Fuzhou City, China[J]. Journal of Geo-Information Science, 2014, 16(3): 490−498.
    [33] Sahar S, Huiwen Z, Xiaoli C, et al. The influence of spatial configuration of green areas on microclimate and thermal comfort[J]. Urban Forestry & Urban Greening, 2018, 34: 85−96.
    [34] Masoudi M, Tan P Y. Multi-year comparison of the effects of spatial pattern of urban green spaces on urban land surface temperature[J]. Landscape and Urban Planning, 2019, 184: 44−58. doi: 10.1016/j.landurbplan.2018.10.023
  • 加载中
图(5) / 表(4)
计量
  • 文章访问数:  117
  • HTML全文浏览量:  48
  • PDF下载量:  28
  • 被引次数: 0
出版历程
  • 收稿日期:  2020-08-24
  • 修回日期:  2021-03-20
  • 网络出版日期:  2021-07-13

目录

    /

    返回文章
    返回