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GEOGRAPHICAL RESEARCH >

2015 , Vol. 34 >Issue 11: 2195 - 2204

DOI: https://doi.org/10.11821/dlyj201511017

Orginal Article

A comparison of the recreational walking environment quality between old and new towns: A case study in Shanghai

  • LIU Jun , 1 ,
  • WANG De , 2 ,
  • ZHU Wei 2 ,
  • WANG Haoyang 2 ,
  • ZHU Chasong 3
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  • 1. China Academy of Urban Planning and Design, Shanghai 200335, China
  • 2. School of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
  • 3. School of Architecture, Xiamen University, Xiamen 361005, Fujian, China

Received date: 2015-05-27

  Request revised date: 2015-08-30

  Online published: 2015-11-15

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《地理研究》编辑部
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Abstract

Walking environment is an important factor in public health and urban planning. To promote higher quality recreational walking environment, one issue requiring further attention is to what extent the walking environment factors are considered important by the pedestrians? This paper aims to contribute to the methods of evaluating and improving walking environment by exploring the underlying mechanisms of pedestrians’ route choice behavior in strolling activities. Stated preference (SP) method is used to reveal the influence of the environment factors on pedestrians' route choices. These environment factors are identified from an extensive literature review and a pilot survey. Hypothetical routes generated by orthogonal design are organized into route choice scenarios and illustrated in graphs. Respondents were required to select the route they prefer to stroll based on its environment factors of certain levels. The choice data are estimated using Discrete Choice Models (DCM) to derive the influence of each factor on the utility of a route. Two different practices are tried in the experiment design from conventional practices. The first is the use of factor level combinations for orthogonal design, which in theory improves the efficiency and effectiveness of the design because according to the nature of DCM, only factor differences matter for the calculation of choice probabilities. The second is the use of graphs in which factors are presented in more realistic and holistic manners for the questionnaire. Testified through internet-based experiments, choices using graphs facilitate respondents' cognition and display different model results from choices described using text only. Residents' walking environment demands differ between old and new built environments, owing to the difference in block scale, residence density and population structure. Data were collected in two selected neighborhoods in Shanghai, Anshan Village and Jiangwan Town as a typical example of old and new built environments respectively. The results reveal that walking environment preferences of the residents from the two neighborhoods are partly different, based on which an LOS-like evaluation method is developed and applied to estimate the utility of any specific route.

Key words： stated preference method; recreational walking environment valuation; Shanghai; comparative research

Cite this article

LIU Jun , WANG De , ZHU Wei , WANG Haoyang , ZHU Chasong . A comparison of the recreational walking environment quality between old and new towns: A case study in Shanghai[J]. GEOGRAPHICAL RESEARCH, 2015 , 34(11) : 2195 -2204 . DOI: 10.11821/dlyj201511017

1 引言

随着生活水平的提高,高质量的休闲步行环境建设受到广泛关注。一方面,出于对健康和品质生活的追求,休闲步行作为最为普遍和有益的有氧锻炼活动,已经被越来越多的市民当作日常生活的一部分;另一方面,以人为本的新型城镇化要求城市重视与日常生活息息相关的社区尺度下的休闲步行环境建设,关注市民生活质量的提高。
什么样的步行环境是舒适的?既有步行环境建设的研究,在理念层面提出了共享街道（Shared Street）、完全街道（Complete Street）等概念[1,2],在操作层面也构建了“技术工具箱”[3,4],但是缺乏对步行环境规划设计措施有效性的讨论。而这一问题离不开对于行人休闲步行环境偏好的理解,行人关注什么样的步行环境要素以及关注程度是怎样的。从环境偏好的视角出发,评估建成环境满足休闲步行活动需求的能力,是针对城市休闲步行环境进行评价的出发点。
大部分研究[5-8]都认为休闲步行活动对于休闲娱乐设施的可达性和街道景观有较强的需求。此外,Van Dyck等[9]还发现居住密度影响休闲步行活动,其他研究也有类似的发现[10-12]。但是,其他环境属性,比如犯罪和交通安全究竟对休闲步行行为产生怎样的作用,其影响机制尚不明了[6,8,13,14]。国内的相关研究刚刚起步,Guo等[15]研究了可感知的环境因素对于老年人社区内部休闲步行活动的影响,发现休闲步行活动的强度主要受到休闲设施可达性、步行基础设施和室内活动空间等因素的影响;卢银桃[16]以上海为例,从日常服务设施步行者使用特征的视角评价了社区的可步行性。
由于国内高密度人居环境的特殊性,步行者在休闲步行环境关注要素和行为需求方面与国外存在较大差异,不能简单地照搬国外的研究结果;而且,国外的研究大多针对历史街区,其在街区尺度、居住密度和建成环境方面均与国内的新建城区步行环境具有较大差异。这些决定了步行体验和行为需求也会有所差别,不能一概而论地对待,需要进行更加深入和精细的研究,比较新旧城区不同步行环境供给条件下休闲步行活动的需求特征。因此,本研究的重点在于比较分析新旧城区休闲步行的环境偏好,并构建相应的评价体系。
上海市杨浦区鞍山新村和江湾新城具有旧城和新区步行环境的一些共性特点,可以作为城市旧城和新区的典型代表进行比较研究,其结论也适宜推广到旧城和新区的步行环境质量评价应用中（表1）。研究地块的选取一方面以城市主次干道为界,避免大量过境交通从地块内部通过,满足一般休闲步行活动的环境要求;另一方面较小的地块面积可以保证地块内部用地功能、居住形态和建筑密度的同质性,利于比较步行环境对步行行为的影响;此外,新旧城区的空间尺度差别较大,为了强化尺度和功能上的可比性,案例地区均选择所属街道的部分居住组团。
Tab. 1 Walking environment types of cases

表1 案例地区的步行环境类型

案例地区 建设年代 占地面积 位置范围 步行环境状况 典型性
鞍山新村 20世纪50年代末 1.51 km2 内环以内,周边被四平路、大连路、中山北二路和内环高架路环绕 走马塘沿区域东侧经过,内部有松鹤公园,南部与大连路一路之隔有和平公园,具有人车混杂、狭窄逼仄、建筑街道界面混乱等旧城步行空间的共性问题 旧城典型代表,步行环境良莠不齐
江湾新城 2000年之后建设完工 3.95 km2 中环和外环之间,被闸殷路、殷高东路、淞沪路和军工路环绕 内部有湿地公园,步行空间宽敞且绿化覆盖率较高,车流量和人流量均不大,但门禁式社区也造成了其以单调围墙为主的街道界面 新区典型代表,步行环境具有均好性
通过比较分析城市旧城和新区的休闲步行者最为关注的环境要素及偏好程度的共性和差异,以及这些共性和差异与其所处的日常休闲步行环境之间的关系;在把握步行环境对步行行为影响机制的基础上,进一步构建基于行为偏好的休闲步行环境评价方法,分别应用于案例地区,进而有针对性地提升步行环境质量,以期鼓励更多的步行行为发生,为快速城镇化阶段其他城市新老城区休闲步行环境建设提供有益的借鉴。

2 研究方法与数据来源

2.1 研究方法

采用叙述性偏好法（stated preference method,SP）进行休闲步行环境质量评价研究。SP法[15,17-21]是让受访者在虚拟路径中选择一条最愿意步行的路径,应用离散选择模型分析各个环境要素影响行为偏好的相对重要程度。相比专家打分法的主观随意性较大的缺陷,SP法将受访者置身于更加自然和客观的决策环境中,根据行人的步行环境偏好来评价休闲步行环境,辨识步行者主要关注的环境要素,以此作为步行环境评价指标,并估计步行者对于这些要素的相对偏好程度,作为指标权重。SP调查设计包括休闲步行环境关注要素甄选、实验设计和调查实施三个部分。

2.2 休闲步行环境关注要素

综合考虑步行环境关注要素的典型性、可感知性、可度量性以及实际步行环境改造中的可实施性等原则,在文献梳理和预调查的基础上,最终确定了14项休闲步行者可能关注的步行环境要素,并定义了水平值（表2）。虽然部分环境要素不具有普遍性,如是否途径公园、街头广场和是否沿河等,但在本研究区域中属于重要的影响要素,其研究成果也说明了其对环境偏好的影响,故纳入实验设计。
Tab. 2 Walking environment choice influencing factors and levels

表2 步行环境选择影响要素及其水平

影响要素 水平1 水平2 水平3
(路径)大交叉口数量（个） 0 1 1,有天桥
(路径)小交叉口数量（个） 少量(≤2) 多量(>2)
人行道界面 绿化围墙 带咖啡座的建筑界面 橱窗建筑界面
是否有绿化隔离 有 无
有效通行宽度（m）① 较宽(>3) 较窄(≤3)
机动车流量大小② 较少 较多
人流量大小③ 较少 较多
遮荫情况④ 较多 较少
是否途经公园 是 否
是否途经街头广场 是 否
路径是否沿河 是 否
是否需要原路返回 是 否
是否有座椅 是 否
步行路径长度（min） 20 45 60

注：① 有效通行宽度：参照《城市步行和自行车交通系统规划设计导则》规定（在居住区支路人行道单侧宽度为2.5~4.5 m）,以3 m为人行道宽窄的分界点。② 机动车流量大小：预调查发现,休闲步行活动的高峰时间与交通出行的早晚高峰有所重叠,早高峰7:00-8:00步行活动占总量的31.41%,晚高峰16:00-18:00占总量的14.84%。采用高峰小时机动车流量作为评价标准。③ 遮荫情况：参考《上海市林荫道评定办法（试行）》规定的林荫道标准,即人行道及非机动车道的绿荫覆盖率达90%以上,四车道以下的机动车道路绿荫覆盖率应达50%以上,四车道及以上的机动车道绿荫覆盖率应达30%以上。

2.3 SP实验设计和实施

SP调查实验设计包括选择方案生成和问卷表达两个步骤。首先将环境要素的水平组合进行正交设计（orthogonal design）,生成虚拟步行路径的选择方案[22,23];然后采用图文并茂[24,25]的表达方式,路段的环境尽量用贴近真实的图像来整合表达,路线中的其他要素则用图标表达,要求受访者根据左右两种步行环境的特征来选择一个较好的步行路线,或者可以都不选,尽量用直观易懂的形式帮助受访者理解（图1）。
Fig. 1 Questionnaire example

图1 调研问卷举例

采用实地问卷调查获得基础数据,调查时间为2013年8月中旬到月底,调查区域基本覆盖案例地区,选择地铁站点、公园绿地、马路街头等作为调查地点。总计获得样本320份,有效样本总数307份,其中鞍山新村147份,江湾新城160份,有效率为95.93%。

3 新旧城区步行环境质量评价体系比较及解释

构建离散选择模型分析SP调查数据。离散选择模型是以随机效用为理论基础的,行人将选择对其效用最大的步行环境。该模型对应的步行环境效用可定义为：
V = ∑ i = 1 n α i x i
式中：V为步行者从该步行环境所能获得的总效用;αi表示步行环境变量xi的效用系数,也是模型所要拟合的系数。除了路径长度以外的变量都是定性变量,因此做了虚拟变量处理。
用Nlogit软件分别对鞍山新村和江湾新城两个地区进行模型拟合。结果显示,并非所有的步行环境变量都具有统计显著性,按照显著度从大到小的顺序依次去掉不显著的变量,每去掉一个都重新建模,直至所有变量都显著为止。最终保留了显著性在0.1以下的变量要素,符号与预期一致（表3）。模型的拟合优度分别为0.23和0.19,说明模型对数据的解释程度较好。
Tab. 3 The fitting result of the environment choice model

表3 休闲步行环境选择行为模型拟合结果

鞍山新村 江湾新城
变量 变量系数值 变量系数值
（路径）小交叉口数量 少量（是=1） - 0.24535**
步行环境界面 咖啡座建筑界面（是=1） 0.23989* 0.34758**
橱窗建筑界面（是=1） 0.30100** 0.24964*
有效通行宽度 较宽（是=1） 0.32680*** 0.31974***
机动车流量大小 较少（是=1） 1.16074*** 1.39621***
人流量大小 较少（是=1） 0.37100*** 0.32877***
遮荫情况 较多（是=1） 0.54764*** 0.32628***
是否途径公园 是（是=1） 0.33360*** -
是否沿河流 是（是=1） 0.22466** -
对数似然数 -350.5376 -509.7804
模型拟合优度 0.23146 0.18826

注：***、**、*分别表示在0.001,0.05,0.1水平上显著,-表示不显著变量。

离散选择模型中通过显著性检验的变量就是筛选和精简之后的城市休闲步行环境质量评价指标,而其对应的系数便是各指标的权重,绝对值越大,说明其在评价体系中重要性越高。由模型结果得到的鞍山新村和江湾新城休闲步行环境质量评价指标和权重有所不同,这是由于两个区域步行者对于步行环境的偏好不同造成的。
鞍山新村休闲步行环境质量评价指标包括步行环境界面、有效通行宽度、机动车流量大小、人流量大小、遮荫情况、是否途径公园和是否沿河流。其中,机动车流量大小、遮荫情况、人流量大小对行人步行环境选择的影响最为显著。不难理解,较大的车流量不仅影响步行环境的安全性,还带来噪声和空气污染问题;上海的夏天较为炎热,步行者会关心遮荫情况,同时绿树成荫本身就是一种景观;人流量较大造成过于拥挤的步行环境,降低了行人的舒适感;逛公园是市民休闲生活的重要组成部分,公园内部优美的环境和钓鱼、棋牌、球类等活动对步行者的吸引力较大;日常生活中流动摊贩、汽车和自行车停车侵占步行空间,有效通行宽度不足影响了行人的正常活动。而是否沿河流变量对步行环境选择也存在一定影响,变量显著程度在5%,河流不仅风景优美,夏季还有降低气温的生态功能,不少行人会在桥头逗留吹风、钓鱼,或沿河道散步。步行环境界面变量的显著程度只在10%。受访者会偏爱建筑界面,因为建筑界面往往意味着更多的功能活动,建筑内会布置日常生活设施,方便市民生活,也会具有更多的活力。
江湾新城休闲步行环境质量评价指标与鞍山新村有所不同,增加了小交叉口数量指标,减少了是否途径公园和是否沿河流两项指标,其他指标的显著程度和符号均与鞍山新村类似。这种休闲步行环境偏好的差异是由以下3个原因造成的：① 休闲步行者的步行环境偏好是基于日常生活经验的,鞍山新村和江湾新城休闲步行环境存在的问题有所差异,而步行者往往会更加关注步行环境相对不足的方面,比如江湾新城街区尺度较大,交叉口数量较多,更加关注交叉口数量指标;② 江湾新城整体步行环境优良,步行环境具有均好性,住区周边已经可以满足休闲步行的需求,而鞍山新村不同路径间步行环境差异较大,步行者对于公园和河流等相对舒适的步行空间的依赖性会更加明显,因此是否途径公园和是否沿河流变量显著;③ 鞍山新村和江湾新城的居住人群结构存在一定差异,不同于工人新村存在一定的老龄化趋势,新型近郊居住区聚集了较多追求生活情调的中青年,因此会更加偏好带有咖啡座的建筑界面,而鞍山新村居民则更加关注是否途径公园和河流等要素。
从指标权重来看,鞍山新村和江湾新城大体趋势类似,局部有所不同。鞍山新村的指标权重从大到小排序依次为机动车流量大小、遮荫情况、人流量大小、是否途径公园、有效通行宽度、步行环境界面和是否沿河流。江湾新城的指标权重从大到小排序依次为机动车流量大小、带咖啡座的建筑界面、人流量大小、遮荫情况、有效通行宽度、建筑橱窗界面和小交叉口数量。无论是旧城还是新区,行人普遍偏好机动车流量较小、人流量较小、遮荫情况较好、步行空间宽敞的休闲步行环境。

4 休闲步行环境评价方法的应用

将SP法构建的休闲步行环境评价体系分别应用于鞍山新村和江湾新城两个案例地区。由现场观察和生活经验可知,在休闲步行过程中,当同一条道路两边的步行环境质量差异不大时,一般靠右步行,同时也会受出发地和到达点的位置影响;当道路两边步行道环境质量差异较大时,经常会选择环境较好的一边步行。故在评价的过程中,选择步行环境较好的一侧进行评价。本案例只涉及居住小区外部的城市道路人行道步行环境,不考虑居住小区内部的步行道,同时以步行环境同质的最长可能路段为基本单元进行分段。首先量化各个路段的步行环境要素,再利用离散选择模型计算步行效用,作为评价结果。
以理论的最优路段效用和最差路段效用为极大值和极小值,平均划分四个取值区间,依次对应步行环境的“优秀”、“良好”、“中等”、“较差”四个等级,使用ArcGIS得到鞍山新村和江湾新城休闲步行环境的整体评价图（图2、图3）。
Fig. 2 Anshan Village walking environment evaluation

图2 鞍山新村休闲步行环境的评价结果

Fig. 3 Jiangwan Town walking environment evaluation

图3 江湾新城休闲步行环境的评价结果

鞍山新村休闲步行环境整体状况一般,各路段良莠不齐;江湾新城整体状况优良,具有一定均好性,这与日常生活经验相符。两者步行环境等级为“较差”的路段多为居住区外围交通性干道,因其机动车流量较大,速度较快,交通噪声和空气污染也会相对严重,且部分路段没有行道树等任何可供遮荫的措施。鞍山新村地区内部步行环境等级为“良好”或“中等”水平的路段较多,空间分布较分散,包括彰武路、本溪路、江浦路、抚顺路、锦溪路、铁岭路、鞍山路、阜新路、江浦路、大连路、控江路的部分或全部路段。其余路段步行环境等级为“优秀”或者“良好”,整体状况较好。尤其是苏家屯路人行道较宽,车流量不大,遮荫状况和绿化景观都很好。江湾新城地区淞沪路虽然也是城市主干道,但由于其机动车流量并不大,遮荫情况较好,人行道有效通行宽度充足等原因,步行环境评价等级为“优秀”。内部步行环境等级为“较差”和“中等”水平的路段集中在东部的国伟路和政悦路。这主要是因为政悦路和国伟路附近尚在施工建设阶段。其余道路的步行环境等级基本为“优秀”和“良好”,尤其是安徒生童话乐园和江湾新城湿地公园附近,非常适合休闲步行活动。
单位时间内通过某条街道断面的人数以及行人停留驻足的场所反映了居民日常生活中对于步行环境的实际偏好。对比基于SP调查的休闲步行环境评价结果与实际居民使用步行环境的情况（图4、图5）,可从侧面反映评价体系的准确性。图4和图5中的步行人数为工作日晚上18:00-19:00每5 min通过街道断面的人数,驻留场所为停留行人超过5人的区域。比较发现,SP获得的休闲步行环境评价结果与居民实际使用特征具有很强的相似性：交通性道路行人较少,苏家屯路、淞沪路等舒适的步行环境行人较多,而且毗邻街头广场和公园的街道空间具有更强的吸引力。相对而言,基于SP调查的步行环境评价弥补了实际观察评价中无法将休闲步行活动剥离出来的缺陷,同时对于各个路段的评价更加细致。
Fig. 4 Revealed preference of Anshan walking environment

图4 鞍山新村步行环境实际使用情况

Fig. 5 Revealed preference of Jiang walking environment

图5 江湾新城步行环境实际使用情况

根据休闲步行者对于不同环境要素偏好程度的差异和现状步行环境问题,可以选择更有效的休闲步行环境提升措施。环境要素偏好程度是通过SP法构建的评价体系的指标权重体现的。鞍山新村地区外围的交通性干道,机动车流量大小较难改变,所以优先选取改善遮荫情况和增加步行空间有效通行宽度的改善措施。而内部步行环境质量的提升多依靠引导机动车车流分流,尽量避免过境交通穿越的策略。江湾新城尚在建设之中,除了闸殷路之外,其他路段机动车流量不大,优先的改善措施主要是增加带咖啡座的建筑界面,提升街道空间的吸引力。此外,由于部分路段尚在建设之中,受行道树成长周期的影响,现状绿化较为有限,但未来的步行环境状况会更好。通过比较鞍山新村和江湾新城评价指标和相对权重具体差别,分析其背后的环境偏好机制,可以为今后更加有针对性地提升新旧城区休闲步行环境质量提供理论依据。

5 结论与讨论

5.1 结论

依据行人对环境要素的偏好特征来评价休闲步行环境质量,这一过程通过SP法实现,并比较分析新旧城区不同步行环境供给条件下的评价指标和相对权重的差异,进一步分别应用到鞍山新村和江湾新城两个案例地区的休闲步行环境评价中。研究发现：
SP法的解释能力较好,是行之有效的评价城市休闲步行环境质量的方法。应用SP法构建评价体系的主要思路是,结合文献综述和预调查,初步构建城市休闲步行环境质量的评价指标;使用SP法调查行人的虚拟步行环境选择行为,构建离散选择模型,根据模型结果中要素属性的显著程度,筛选和精简评价指标,而要素属性的系数便是指标的相对权重。
新旧城区不同休闲步行环境供给条件下,评价指标和相对权重有所不同,显示出步行者环境偏好的共性和差异。鞍山新村和江湾新城分别代表了步行环境供给的不同类型,无论是旧城还是新区,行人普遍偏好机动车流量较小、人流量较小、遮荫情况较好、步行空间宽敞的休闲步行环境。评价体系存在差异的原因有三个：一是,步行环境偏好是基于日常生活经验的,步行者通常关注步行环境中相对不足的方面,而鞍山新村和江湾新城整体步行环境特征和存在问题有所不同;二是,江湾新城步行环境具有均好性,住区周边已经可以满足休闲步行的需求,而鞍山新村步行者对于公园和河流等相对舒适的步行空间的依赖性会更加明显;三是,居住人群结构不同,不同人群对于步行环境的感知和评价有所差异。
鞍山新村和江湾新城休闲步行环境评价结果与日常生活经验相符。两者步行环境等级为“较差”的路段多为不适宜休闲步行活动的居住区外围交通性干道。此外,鞍山新村街道内部步行环境等级为“中等”或“良好”水平的路段较多,空间分布较为分散。江湾新城街道内部部分路段尚在建设之中,现状绿化较为有限,但其余道路的步行环境等级基本为“优秀”和“良好”,尤其是安徒生童话乐园和江湾新城湿地公园附近,非常适合休闲步行活动。
由于现状步行环境和步行者行为偏好的地区差异性,案例地区相应的改善措施的优先次序也有所差别。鞍山新村外围交通性干道采取的措施为改善遮荫情况和增加步行空间有效通行宽度,而内部步行环境质量的提升多依靠引导机动车车流分流。江湾新城最有效的改善措施是增加带咖啡座的建筑界面。

5.2 讨论

本研究的目的是比较分析新旧城区休闲步行环境关注因素及偏好程度,评价旧城、新区的休闲步行环境质量,并提出针对性的改善措施。在新旧城区不同休闲步行环境供给条件下,步行者的环境偏好有所不同,使用SP法获得的步行环境质量评价指标体系和相对权重也会存在一定差异。这从侧面说明,很多只调研一个地区就推论出广泛的评价指标和权重的做法是有缺陷的,忽略了步行环境、街区形态和人口结构等其他因素造成的不同地区环境偏好的差异性。

The authors have declared that no competing interests exist.

References

Publishing order | Descend order by publishing year | Descend order by cited within
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[Zhao Peng, Hujiwara Akimasa, Sugie Laining.SP survey method in the application of traffic prediction. Journal of Northern Jiaotong University, 2000, 24(2): 29-32.]

[24]
Ortúzar J D.Estimating individual preferences with flexible discrete-choice-models. Food Quality and Preference, 2010, 21(3): 262-269.lt;h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">Discrete-choice-models have come a long way since the field erupted in the seventies with the seminal work of McFadden and colleagues at Berkeley. For more than 25&#xA0;years the multinomial logit (MNL) model and its close relative, the hierarchical or nested logit (NL) model (a generalization that allowed treating correlated alternatives grouped in nests, the simultaneous brain child of <span id="bbib46"><a href="#bib46" id="ancbbib46" class="intra_ref">Williams (1977)</a></span> and <span id="bbib18"><a href="#bib18" id="ancbbib18" class="intra_ref">Daly &amp; Zachary (1978)</a></span>) reigned supreme, using mainly revealed preference data. At the end of the 90s the modeller&rsquo;s tool kit expanded considerably with the installation of both stated preference data, as a strong ally to help treating the problems posed by new alternatives and latent or secondary variables, and the most flexible member of the family, the mixed logit (ML) model, that allows considering two remaining deficiencies of the old guard, heteroskedasticity and taste variations. This paper provides a glimpse of the field and speculates on the potential use of these methods to complement sensory work in the effort to better understand customer preferences.</p>

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[25]
Todorova A, Asakawa S, Aikoh T.Preferences for and attitudes towards street flowers and trees in Sapporo, Japan. Landscape and Urban Planning, 2004, 69(4): 403-416.lt;h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">The benefits of street vegetation, in particular the importance of trees, for urban dwellers have been given wide attention. There is, however, a lack of research on flowers as an element of street vegetation. This paper explores preferences for various street-planting models, particularly those with different compositions of flowers, with or without trees. Eighty-one residents of Sapporo evaluated 59 photomontage simulations and answered a questionnaire concerning their attitudes to street flowers. Results revealed trees to be the factor with the greatest influence on preference. Among possible elements for the space beneath trees from a choice including soil, grass, hedge and flowers, flowers were the most favoured. In particular, low and ordered compositions of brightly coloured flowers were the most preferred. Tall flowers were not found to be either attractive or appropriate for streetscapes in this case study. A factor analysis of the variables related to attitudes towards street flowers revealed the following five factors: &ldquo;psychological benefits and aesthetic value&rdquo; &ldquo;natural&ndash;environmental&rdquo; &ldquo;practical concerns&rdquo; &ldquo;effort to maintain&rdquo; and &ldquo;non-aesthetic&rdquo;. The highest rated items were all related to the aesthetic and psychological benefits of street flowers. Flowers were the most preferred element beneath street trees and were seen as not only contributing to the aesthetic quality of a street but as also having a positive influence on psychological well-being.</p>

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