Community Stories: Explaining Resistance to Street Tree-Planting Programs in Detroit,Michigan, USA

Non-profit organizations are key actors in urban and community forestry (UCF) initiatives, and sometimes city residents resist their efforts. Between 2011-2014, 24 percent of residents offered a street tree in Detroit, Michigan, USA submitted a “no-tree request.” Differing views on decision-making emerged as a main reason for resistance to tree planting. This study used interviews with city residents, and those within a non-profit organization, between 2014-2016 to understand reasons for conflict over decision-making between these groups. Heritage narratives, or selective representations of the city’s history and character, helped explain conflict over tree planting. Residents who wanted greater decision-making power in tree planting assumed they would be responsible for stewardship, reflecting their historical experiences within the city. The organization’s dominant heritage narrative emphasized that residents held misperceptions of trees based on negative past experiences, and required education on benefits of trees. Recommendations for integrating heritage narratives into UCF efforts are provided.     

广州华侨新村低密度住宅区庭院的树木和景观研究*

对广州华侨新村低密度住宅区庭院树木的组成、结构、空间格局、树木与生境的关系,以及私人庭院树木与公共绿地的不同特点进行了研究。结果表明:华侨新村庭院树木的种类多样性很高,共有114个树种。与广州城市行道树相比,华侨新村的乡土树种和果树比例较高。在调查的树木中84.75%的树木没有结构损伤现象,只有1.5%的树木生长较差。私人庭院内的树种较为分散,有45种树木为每个庭院仅一棵的单生种,有67.1%的庭院其树种在5种或以上。树木在街道的空间分布则有相对集中的趋势。庭院的大小是影响树木生长的重要条件,在有限空间的庭院内种植过多的树木是造成树木和环境关系紧张的重要原因。     

建设广州国际大都市的市区街道绿化

本文运用生态学方法，分析了广州市行道林生物群落、生态质量、空间分布特征及生态环境作用。在此基础上，提出了建设广州国际大都市街道绿化的建议。     

杭州商业街道空间布局形态关键要素对周边风环境的影响

利用基于计算流体力学（CFD）理论的数值模拟软件,在不影响街道连续性面貌的前提下,通过控制变量法分别改变街道贴线率、街道界面密度、街道高宽比3个关键要素的数值来观察街道风环境的变化情况。结论主要有： 街道内的风速大小随着街道贴线率的增大呈抛物线趋势变化,先增大后减小,在街道贴线率接近70%时,城市街道内风速达到最大; 随着界面密度的不断减小,城市街道内各个测点的风速变化的幅度越来越大,这样会让在其中行走的行人感受到强烈的风速变化,舒适度大为下降; 城市街道内的平均风速和街道高宽比成反比例关系。     

Street networks in relation to landforms：Implications for fast-growing cities

In addition to socio-economic factors,major landforms may affect the city structure and urban form. Here we show that landforms have significant effects on the city shape and street patterns of the fast-growing Iranian cities of Dezful (a river) and Khorramabad (mountains and valleys),but no clear effects on the cities of Yazd and Nain. Also,where the street orientation is peaked,the Gibbs/Shannon entropy (a measure of dispersion or spread) is low,but increases as the distribution becomes more uniform because of landform constraints. The streets in the old inner parts of all the cities are,on average,shorter and denser (more streets per unit area) than the streets of the newer outer parts. The entropies of the outer parts are also greater than those of the inner parts,implying that the street-length distribution gradually becomes more dispersed or spread as the city expands. All these cities have been fast growing in the past decades,with the newer outer parts expanding rapidly. As shown here,the rapidly formed outer parts (with greater dispersion in street patterns) have significantly different textures from those of the older inner parts,indicating different functionality and growth processes. These quantitative methods for street-network analysis can be used worldwide,particularly for analysing the effects of landforms on city shape and texture.     

Urban landscape as mirror of ethnicity: trees of the South Plains

The literatures on urban forestry, environmental justice, and Marxist urban political ecology are considered through empirical attention to the localized racial and ethnic politics which spatially differentiate urban socio-natural landscapes. In the American Southwest, urban landscapes reflect a history in which Anglo Whites were able to distance themselves from spaces of production while gaining access to superior residences and environmental amenities in spaces of reproduction; ethnoracially marginalized Others were treated as necessary yet disfavored populations, thus constituting a segregated mode of production. In this study, we investigate the association between tree canopy cover and the location of urban ethnic minority populations with a focus on the arid Southern High Plains city of Lubbock, Texas. Using data from color infrared aerial photography and block-group demographic indicators from the 2010 US Census, we analyze the city’s arboreal landscape with a mix of methods—hierarchical regression, archival research, and field observation. Results confirm that a lack of tree cover in minority neighborhoods is a symptom of broader environmental inequalities in which contemporary segregation patterns reflect a history of residential and land-use zoning with the socio-natural relations of planting and sustaining urban trees.     

与地形相关的街道网络分析及其对快速增长型城市的意义(英文)

In addition to socio-economic factors, major landforms may affect the city structure and urban form. Here we show that landforms have significant effects on the city shape and street patterns of the fast-growing Iranian cities of Dezful(a river) and Khorramabad(mountains and valleys), but no clear effects on the cities of Yazd and Nain. Also, where the street orientation is peaked, the Gibbs/Shannon entropy(a measure of dispersion or spread) is low, but increases as the distribution becomes more uniform because of landform constraints. The streets in the old inner parts of all the cities are, on average, shorter and denser(more streets per unit area) than the streets of the newer outer parts. The entropies of the outer parts are also greater than those of the inner parts, implying that the street-length distribution gradually becomes more dispersed or spread as the city expands. All these cities have been fast growing in the past decades, with the newer outer parts expanding rapidly. As shown here, the rapidly formed outer parts(with greater dispersion in street patterns) have significantly different textures from those of the older inner parts, indicating different functionality and growth processes. These quantitative methods for street-network analysis can be used worldwide, particularly for analysing the effects of landforms on city shape and texture.     

Street networks in relation to landforms: Implications for fast-growing cities简

In addition to socio-economic factors, major landforms may affect the city structure and urban form. Here we show that landforms have significant effects on the city shape and street patterns of the fast-growing Iranian cities of Dezful （a river） and Khorramabad （moun- tains and valleys）, but no clear effects on the cities of Yazd and Nain. Also, where the street orientation is peaked, the Gibbs/Shannon entropy （a measure of dispersion or spread） is low, but increases as the distribution becomes more uniform because of landform constraints. The streets in the old inner parts of all the cities are, on average, shorter and denser （more streets per unit area） than the streets of the newer outer parts. The entropies of the outer parts are also greater than those of the inner parts, implying that the street-length distribution gradually becomes more dispersed or spread as the city expands. All these cities have been fast growing in the past decades, with the newer outer parts expanding rapidly. As shown here, the rapidly formed outer parts （with greater dispersion in street patterns） have significantly different textures from those of the older inner parts, indicating different functionality and growth processes. These quantitative methods for street-network analysis can be used worldwide, particularly for analysing the effects of landforms on city shape and texture.     

土地利用对街头抢劫影响的空间分异模式：以H市为例

选取H市中心城区2009年和2010年发生的街头抢劫案件为研究对象,构建地理加权泊松回归GWPR模型,探讨不同性质土地利用对案件影响的空间差异性。研究表明,各类用地与街头抢劫的关系存在显著的空间异质性。其中,位于中心区外围的传统居住区和部分新建社区等居住用地对街头抢劫存在显著的负向影响;商业服务业设施用地对街头抢劫的影响总体上显著性不强,但与其中的商业设施点类型密切相关,独栋高层的商业综合体会使犯罪数量下降,而临街商铺形式的商业设施点则是犯罪高发区域;工业用地仅对老城区的街头抢劫产生正向影响;公园绿地总体上与街头抢劫案件呈负相关性,但城市开敞绿地多的地方案件数量也较多;交通设施用地与街头抢劫的关系则受到交通设施、道路等级、路网形态的影响。最后通过聚类分析发现,土地利用对案件影响的主导因素的空间分异模式与不同的城市功能分区有一定的对应关系,可以对每个功能分区根据其街头抢劫发生的主导因素制定相应的土地利用规划导则。     

Patterns and dynamics of urban forests in relation to land use and development history in Guangzhou City, China

Trees in cities display a varied pattern that is often moulded by a city's physical fabric and its evolution through time. The town plan expressed in spatial dimension as land use, and in temporal sense as development history, furnishes a framework to evaluate the intricate association between city and trees. Guangzhou city, the premier metropolis of south China, has been established for 2800 years, and has a long history of urban greening and heterogeneous land use. Five urban districts, which represent old, middle-aged and young stages of development and cover the bulk of the city's built-up zones, form the study area. Interpretation of aerial photographs is used as a basis to classify the urban forest into three types, and to design a sampling scheme for studying trees in urban parks, institutional grounds and roadsides. District history has bequeathed a plethora of configurations in terms of buildings, roads and land uses, accompanied by plantable spaces of dissimilar dimensions, geometry and quality. The districts display diverse tree attributes such as frequency, density and species diversity. Young districts, with lower density, more institutional uses and wider roads, present more opportunities for greening. Recent shifts in landscape fashion have introduced a significantly different treescape. A few exceptionally large parks and institutional sites play a pivotal role in the city's tree assets. Parks, roadsides and institutional forests have different tree-stocking rates and species assemblages. Implications for future planting and management of urban trees in different situations, and for the greening of other cities in China, and other developing countries, are explored.     

基于街景影像和手机信令数据的城市街道安全性研究

城市化进程加快导致街道安全性问题突出,已有研究利用城市视觉要素刻画街道安全感空间分布,忽略了街道真实安全性与安全感间的差异。该文利用街景影像和手机信令数据,结合K-means聚类算法与笛卡尔积运算模型减少“安全感知差异”,以长沙市主城区为研究案例,得到白天、夜晚及总体城市街道安全性分布:1)长沙市主城区安全感指数随圈层数增加呈波动递减趋势,主要原因是建筑视觉要素占比下降较快以及天空视觉要素占比逐步上升;2)长沙市主城区呈双圈层结构,白天高安全性、夜晚低安全性以及总体安全性最低的区域主要分布在主城区中心,具有明显的聚集现象。该研究通过对城市街道安全性和低安全性街道的分析提出街道优化建议,为城市规划提供参考。     

厦门旧城建设步行街区的初步研究

以厦门旧城区西南部为例,对商业街土地利用和商服业现状作了详尽的调查和分析,在阐述旧城区商业街存在总体地位下降,以服装店为主的零售商业功能过于突出,购物环境容量不足等现实问题的基础上,提出以“步行街区”作为厦门旧城商业街更新发展的对策,并据此对步行街区建设涉及到的部分问题进行了探讨。     

街景图片识别城市贫困的适用性——基于广州市中心城区的验证

以广州市为例，选取中心4个区6 670个采样点（涵盖121个社区）的百度街景图片，从城市建成环境特征探讨了城市贫困识别的可能。首先，训练基于深度神经网络的街景图片分类模型后，对街景要素进行语义分割，并通过缓冲区分析统计社区尺度的街景指标；其次，经主成分分析法提取出建筑围合感、植被围合感、天空开阔感和道路开阔感4个街景主因子，并验证其与多重贫困指数（IMD）的相关性；最后，通过采用简单随机抽样法选取61个社区，构建街景预测的多元线性回归模型，对剩余60个社区进行贫困预测，验证街景指标测度城市贫困的度量精度。结果发现，案例社区的多重贫困指数（IMD）与建筑围合感呈正相关，与植被围合感、天空开阔感、道路开阔感呈负相关；从整体看来，街景预测结果与传统城市贫困测度的空间规律基本相符，而且结果通常比传统测度的城市贫困程度高。这是因为受测度内容、社区类型、街道属性等方面的影响，街景识别方式比较适用于判断建成环境较差的贫困社区。街景图片预测有利于刻画城市贫困人群真实的生活环境，便于对城市建成区进行及时监测，在一定程度上可以与传统城市贫困测度相互校正、弥补不足。     

Modeling Environmental Concern for Urban Tree Protection Using Biophysical and Social Psychological Indicators

Urban forest management is being increasingly recognized as a viable policy vehicle for improving community health, sustainable development, and well-being for city dwellers. To improve our understanding of public concern for the local urban forest, a theoretical framework employing concepts traditionally explored in social–psychological and environmental concern studies was tested using data from a public opinion survey of 800 homeowners living in a major urban area in Southern Appalachia, USA. Publicly available geographic information system (GIS) data were analyzed to measure tree canopy density around survey respondents’ properties. Structural equation modeling was used to test the validity of the hypothesized relationships among the survey-derived constructs and the spatial data as predictors of public support for urban forest protection policy. The results suggest that homeowners living around urban trees place greater importance on various attributes of trees, and that tree knowledge and experience are indirectly and positively related to support for urban forest protection.     

DELIMITING THE PHYSICAL CITY: DISPARITIES BETWEEN VARIOUS METHODS OF CALCULATING POPULATION DENSITIES*

The legal city and the urbanized area fail to depict accurately the physical area of urban development and therefore prevent an accurate calculation of population densities. When underbounding occurs, densities tend to be unrealistically high and with overbounding they are low. Delimitations made by air photo interpretation demonstrate that the physical city, measured on a 21/2 acre scale of generalization, provides a more accurate basis for calculating population densities of urban areas than either the legal city or urbanized area because the bounding problems are eliminated.     

Street as a big geo-data assembly and analysis unit in urban studies: A case study using Beijing taxi data

Quantitative research of urban geography has benefited greatly from the rapid development of big geo-data. Spatial assembly is an essential analytical step to summarize and perceive geographical environment from individual behaviours. Most research focuses on the methodology of how to utilize the big data, while the adopted spatial units for data aggregation remain areal in nature. This article conceptually proposes an idea of sensing cities from a street perspective, emphasizes the significance of street units in quantitative urban studies. Using a three-month taxi trajectory dataset and the major streets in Beijing, we explore the spatio-temporal patterns of urban mobility on streets, cluster streets into nine types based on their dynamic functions and capacities. Additionally, we discuss the differences and connections between the linear street unit and traditional areal units, investigate the possibility of uncovering urban communities using streets, and point out the complexity of streets. We conclude that street unit as a supplement to areal units, is able to effectively minify the modifiable areal unit problem (MAUP), sense urban dynamics, depict urban functions, and understand urban structures.     

Defining and generating axial lines from street center lines for better understanding of urban morphologies

Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least set of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space syntax, a theory developed by Bill Hillier and his colleagues for characterizing the underlying urban morphologies. For a long time, generating axial lines with the help of some graphic software has been a tedious manual process that is criticized for being time consuming, subjective, or even arbitrary. In this article, we redefine axial lines as the least set of individual straight line segments mutually intersected along natural streets that are generated from street center lines using the Gestalt principle of good continuity. Based on this new definition, we develop an automatic solution for generating the newly defined axial lines from street center lines. We apply this solution to six typical street networks (three from North America and three from Europe) and generate a new set of axial lines for analyzing the urban morphologies. Through a comparison study between the new axial lines and the conventional or old axial lines and between the new axial lines and natural streets, we demonstrate with empirical evidence that the newly defined axial lines are a better alternative for capturing the underlying urban structure.     

Incorporating vegetation into visual exposure modelling in urban environments

Visual exposure modelling establishes the extent to which a nominated feature may be seen from a specified location. The advent of high-resolution light detection and ranging (LiDAR)-sourced elevation models has enabled visual exposure modelling to be applied in urban regions, for example, to calculate the field of view occupied by a landmark building when observed from a nearby street. Currently, visual exposure models access a single surface elevation model to establish the lines of sight (LoSs) between the observer and the landmark feature. This is a cause for concern in vegetated areas where trees are represented as solid protrusions in the surface model totally blocking the LoSs. Additionally, the observer's elevation, as read from the surface model, would be incorrectly set to the tree top height in those regions. The research presented here overcomes these issues by introducing a new visual exposure model, which accesses a bare earth terrain model, to establish the observer's true elevation even when passing through vegetated regions, a surface model for the city profile and an additional vegetation map. Where there is a difference between terrain and surface elevations, the vegetation map is consulted. In vegetated areas the LoS is permitted to continue its journey, either passing under the canopy with clear views or partially through it depending on foliage density, otherwise the LoS is terminated. This approach enables landmark visual exposure to be modelled more realistically, with consideration given to urban trees. The model's improvements are demonstrated through a number of real-world trials and compared to current visual exposure methods.     

Combined vegetation volume and “greenness” affect urban air temperature

Cities are often substantially warmer than their surrounding rural areas. This ‘urban heat island effect’ can negatively affect the health of urban residents, increase energy usage, and alter ecological processes. While the effect of land use and land cover on urban heat islands has been extensively studied, little is known about the role of vegetation volume or built-area volume about this phenomenon. We ask whether the 3-dimensional structure of urban landscapes influences variations in temperature across a city. Using heights-above-ground information derived from LiDAR data and the Normalized Difference Vegetation Index (NDVI) calculated from multispectral (4 band: Blue, Green, Red, and Near Infrared) aerial images, we estimated vegetation volume and built-area volume (non-vegetated) in Chicago, Illinois (USA). Daily minimum temperature data were obtained from 36 weather stations for summer 2011. The differences in urban air temperature across the study area were as large as 3 °C. Maximum likelihood models indicated that a combination of NDVI and vegetation volume best predicted nighttime temperature in Chicago, and that vegetation growing within 250–500 m of the weather station was most influential. Our results indicate that vegetation in “the matrix”, i.e. the area outside parks and preserves, is important in temperature mitigation since the majority of the vegetation volume in the study area occurs within residential, commercial/industrial, and institutional land uses. However, open space, which covers only 15% of the study area, has nearly as much total vegetation volume as residential land, which covers 61% of the study area. Clearly, both large wooded parks within a city and large trees scattered across residential areas are needed to best mitigate the urban heat island effect.     

大连城市绿地可达性对房价影响的差异性分析

研究房价、遥感影像等多源数据,采用邻域分析法和地理加权回归模型分析大连市中山区绿地可达性及其与房价之间的空间相关性。结果表明：① 房价均价14 745.35元/m²,呈环状分布,由沿海向内陆衰减、桂林街道起中心向外围递减;② 研究区内可达性最好的绿地类型是街旁绿地,绿地可达性总体水平最高街道是桂林街道;公园绿地可达性最好的住宅区分布在昆明街道和桃源街道,街旁绿地可达性最好的住宅区分布在桂林街道,附属绿地可达性最好的分布在老虎滩街道,其他绿地可达性最好的分布在桃源街道。③ 不同类型绿地可达性对房价影响作用程度递减排序为：附属绿地、街旁绿地、公园绿地和其他绿地;附属绿地、街旁绿地和其他绿地与房价呈现空间正相关,随着到达绿地距离降低,房价呈现增长趋势;公园绿地与房价呈现负相关,随着到达公园绿地的距离降低,房价呈现衰减趋势。