新旧城区休闲步行环境质量比较——以上海市鞍山新村和江湾新城为例

doi:10.11821/dlyj201511017

摘要/Abstract

摘要：

城市的旧城与新区由于街区尺度、居住密度和人群结构等方面的不同,居民的休闲步行行为需求也存在较大差异。选择上海市杨浦区鞍山新村和江湾新城作为旧城和新区的典型代表,以307份调查问卷为基础数据,应用叙述性偏好法,比较分析新旧城区居民休闲步行环境的关注要素和偏好程度,以此为基础构建休闲步行环境评价方法,并分别应用在案例地区。研究表明：旧城、新区居民对休闲步行环境的需求相似又相异,通过离散选择模型构建的休闲步行环境评价指标和权重也会有所不同,从侧面说明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;应用该评价方法,鞍山新村和江湾新城休闲步行环境定量评价结果与日常生活经验相符。

关键词: 叙述性偏好法, 休闲步行环境质量, 上海, 比较研究

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

刘珺, 王德, 朱玮, 王昊阳, 朱查松. 新旧城区休闲步行环境质量比较——以上海市鞍山新村和江湾新城为例[J]. 地理研究, 2015, 34(11): 2195-2204.

Jun LIU, De WANG, Wei ZHU, Haoyang WANG, Chasong ZHU. 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.

图/表 8

表1

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

表2

图1

表3

图2

图3

图4

图5

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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

		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^**
步行环境界面	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