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文摘
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随着城市化进程的加快,城市热岛问题日益严重,对人类健康和城市可持续发展产生了巨大威胁.植被可有效遮蔽阳光直射,并通过蒸腾作用降低气温,是改善局部热环境的重要途径之一.开展植被对建筑物温度的调控效应的研究,对于理解城市热岛成因、缓解城市热环境恶化等方面都有重要意义.然而,当前研究往往是在遥感影像的基础上进行的,缺乏植被结构信息,同时,受制于有限的空间分辨率,研究大多在城市尺度下开展.在中小尺度上定量地研究植被冠层密度对建筑物温度的影响仍然具有一定挑战性.鉴于此,本文使用激光雷达(Light Detection and Ranging, LiDAR)获取的高分辨率冠层密度数据,在楼间尺度和街区尺度下开展圣罗莎市三维植被结构与单体建筑物表面温度之间定量关系的研究,分析不同尺度下植被冠层的降温特征及其在局部环境中的降温贡献.结果表明:植被对建筑物的降温作用与其周围的冠层密度有密切关系:冠层密度需达到17%才能起到有效的降温作用,其中在中小尺度上冠层密度分别高于30%和40%时,能最大限度发挥植被的温度调控功能;当冠层密度相同时,2个尺度下的温度变化显著不同:随着冠层密度的增加,街区尺度下的屋顶温度比楼间尺度下的屋顶温度平均下降了0.89 ℃;中小尺度下的屋顶温度变化不仅受到其周围植被结构的影响,还与整体热环境状况有关.本文的研究思路与结果有助于在有限的城区土地资源上合理规划绿地建设,构建可持续的人类宜居环境. |
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其他语种文摘
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With the acceleration of urbanization, urban heat island (UHI) effect has become an increasingly serious problem, which poses a great threat to public health and urban sustainability. Vegetation can lower the air temperature by reflecting direct sunlight and through the process of evapotranspiration, and hence plays a key role in improving local thermal environments. Investigating the effect of vegetation on regulating building temperature is very useful for understanding the principle of urban heat island and mitigating the deterioration of urban thermal environment. However, most previous studies are based on remote sensing imagery, which lacks three-dimensional information on vegetation structure. Additionally, these studies are mainly carried out at the urban scale due to the limitation of spatial resolution. Therefore, it remains challenging to quantitatively investigate the effects of vegetation canopy structure on building temperature at small and medium scales. In this paper, we quantitatively investigated the relationship between the LiDAR-derived 3D vegetation structure (canopy density, CD) and the rooftop surface temperature (RST) at the city-block (medium) and individual building (small) scale. We improved the Building Thermal Functional Area model (BTFA). Considering the spatial and quantity characteristics of buildings in Santa Rosa, the optimal sizes of the small and medium thermal function areas were estimated. Then the vegetation canopy density around the buildings at two scales were calculated. The cooling capacity of CD was analyzed by nonlinear fitting model and other statistical methods. Moreover, we used spatial autoregression model to analyze the contribution of CD to lower the rooftop temperature under the interaction of various factors. Results show that the cooling effect of vegetation on buildings is closely related to the canopy density around them: the minimum threshold of 17% is required to achieve effective cooling effect, while 30% and 40% are the optimal thresholds at medium and small scales, respectively. Additionally, changes of RST vary at different scales with the same canopy density. The decrease of RST at the medium scale is on average 0.89 ℃ lager than that at the small scale. The findings suggest that the planning of urban green space should be considered comprehensively in different scales. Moreover, the RST changes at small and medium scales are affected by not only the vegetation structure nearby the buildings but also the overall thermal environment. The methods and results of this paper are helpful to better plan green spaces on the limited urban land resources and build a more sustainable human livable environment. |
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来源
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地球信息科学学报
,2019,21(7):1097-1108 【核心库】
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DOI
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10.12082/dqxxkx.2019.180547
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关键词
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LiDAR
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城市热环境
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中小尺度
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冠层密度
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屋顶表面温度
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调控效应
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圣罗莎市
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地址
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1.
首都师范大学, 三维信息获取与应用教育部重点实验室, 北京, 100048
2.
首都师范大学资源环境与旅游学院, 北京, 100048
3.
中山大学地理科学与规划学院, 广州, 510275
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1560-8999 |
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学科
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环境科学基础理论 |
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基金
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地表载荷作用下MTINSAR城市地面沉降监测及时空多尺度演化规律挖掘
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文献收藏号
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CSCD:6538861
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