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Disentangling the effects of urban form and socio-demographic context on street tree cover: A multi-level analysis from Montréal

机译:解开城市形态和社会人口统计背景对街道树木封面的影响:蒙特拉尔的多级分析

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摘要

Street trees provide a wide range of benefits for cities. Street tree cover (STC) is explained by urban form, social stratification and lifestyle theories that operate at multiple scales. In this paper we examine how the urban form (street characteristics), social stratification and lifestyle (socio-demographics) account for variations of STC in Montréal. Tree cover was identified from Quickbird images and then overlaid on street segments to compute the STC. Each street segment was nested in a census tract. We used 2-level models with mixed effects and interactions (between street attributes and socio-demographic variables) while introducing a spatial term. Political, socio-economic or other explanatory factors operating at the tract level can potentially explain 17.6% of the variation of STC. Overall, the street characteristics explained more variation in STC than the socio-demographic context. Lifestyle is less important than social stratification. Street length is positively associated with STC; street width and the percentage of duplexes and triplexes are negatively associated with STC, while construction age has a u-shaped effect on STC. Interactions show that STC is higher in expensive and highly-educated areas that have residential streets or streets with large setback (sidewalk). Areas predominantly comprised of low-income households could have higher or lower STC depending on the number of buildings and the percentage of duplexes and triplexes. Streetscape and socio-demographic contexts intertwine to create complex patterns of STC. Greening programs should be designed carefully according to local contexts since certain types of greening can lead to gentrification and displacement of low-income households.
机译:街道树为城市提供广泛的福利。街道树木封面(STC)由城市形态,社会分层和生活方式理论解释,这些理论在多种尺度上运行。在本文中,我们研究了城市形态(街道特征),社会分层和生活方式(社会人口统计学)算法在蒙特利尔STC的变化。从QuickBird图像识别树盖,然后在街道段上覆盖以计算STC。每个街道段都嵌套在人口普查。我们在引入空间术语时使用了2级模型(在街道属性和社会人口统计变量之间)的混合效果和交互。在道路水平上运营的政治,社会经济或其他解释因素可能会解释STC变异的17.6%。总的来说,街道特征在STC中解释了比社会人口上下文更多的变化。生活方式不如社会分层重要。街道长度与STC呈正相关;街道宽度和双链体和三重复合物的百分比与STC负相关,而施工时代对STC具有U形效果。互动表明,STC在昂贵且受过高等教育的区域较高,其中有大型挫折(人行道)的住宅街道或街道。主要由低收入户口组成的地区可能具有更高或更低的STC,具体取决于建筑物的数量和双链体和三种复合物的百分比。街景和社会人口统计背景intertwine以创建复杂的STC模式。由于某些类型的绿化可以导致低收入家庭的良好,因此应根据当地背景仔细设计绿化计划。

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