地理科学进展 ›› 2019, Vol. 38 ›› Issue (6): 807-817.doi: 10.18306/dlkxjz.2019.06.002
收稿日期:
2018-10-18
修回日期:
2019-03-21
出版日期:
2019-06-28
发布日期:
2019-06-27
通讯作者:
肖龙珠
作者简介:
第一作者简介:刘吉祥(1989— ),男,湖南娄底人,博士生,主要从事城市健康地理与交通出行研究。E-mail:
基金资助:
Jixiang LIU1(), Jiangping ZHOU1, Longzhu XIAO2,*(
), Linchuan YANG1
Received:
2018-10-18
Revised:
2019-03-21
Online:
2019-06-28
Published:
2019-06-27
Contact:
Longzhu XIAO
Supported by:
摘要:
步行是一种重要的交通方式,也是体力活动的重要组成部分。然而,现代城市居民步行频率持续下降,相应地带来体力活动水平的持续降低,伴随着肥胖等慢性非传染病广泛蔓延,值得警惕。西方很多研究证实了建成环境(常以“3D”或“5D”等模型刻画)对步行行为的影响。基于西方的结论对于中国香港、北京和上海等具有与西方城市大相迥异的建成环境的城市是否适用?不同的人群由于具有不同的社会经济属性和生活节奏、习惯,其步行行为受建成环境的影响在方向、强度上是否存在差异?为解决上述问题,论文以香港为案例地,以职员和学生2类人群的步行通勤通学行为为研究对象,利用香港人口普查数据、Open Street Map数据以及中原地图数据等,采用传统的线性回归和空间计量模型进行分析,发现:①通勤通学距离是影响职员和学生步行通勤通学行为的最重要变量;②以“5D”模型刻画的建成环境对香港居民步行通勤通学行为的影响,与西方情境下的结论存在一定的差异,如,在香港,距地铁站的距离与职员和学生步行通勤比例相关性均不显著;③建成环境对步行通勤通学行为的影响,在职员与学生两类人群之间在方向和强度上存在显著差异。例如人口密度与职员步行通勤比例负相关,但与学生步行通学比例正相关。研究凸显了在“建成环境-交通行为”关系研究中情境(context)和人群区分(segmentation)的重要性。
刘吉祥, 周江评, 肖龙珠, 杨林川. 建成环境对步行通勤通学的影响——以中国香港为例[J]. 地理科学进展, 2019, 38(6): 807-817.
Jixiang LIU, Jiangping ZHOU, Longzhu XIAO, Linchuan YANG. Effects of the built environment on pedestrian communing to work and school: The Hong Kong case, China[J]. PROGRESS IN GEOGRAPHY, 2019, 38(6): 807-817.
表1
变量及数据描述"
变量 | 变量描述 | 均值 | 标准差 |
---|---|---|---|
社会经济属性变量(控制变量) | |||
女性百分比 | 每个TPU中女性占总人口百分比 | 0.5 | 0.04 |
平均年龄 | 居民年龄平均值 | 41.8 | 3.2 |
平均家庭收入 | 家庭平均月收入 (港币) | 33294 | 29762 |
平均家庭规模 | 家庭人口数 | 2.9 | 0.4 |
建成环境属性变量(解释变量) | |||
在TPU内部通勤的百分比 | 学生/职员在TPU内部通勤通学的人数占全部学生/职员的百分比 | 0.46/0.17 | 0.22/0.10 |
人口密度 | 每km2人口数 | 28963 | 33422 |
容积率 | 总建筑面积与用地面积比值 | 1.1 | 1.3 |
土地利用混合度 | 公式 | 0.3 | 0.3 |
公交站点密度 | 每km2公交站数量 | 27 | 33 |
道路交叉口密度 | 每km2街道交叉口数量 | 102 | 103 |
距最近地铁站距离 | 从TPU地理中心到最近的地铁站的距离 (m) | 1868 | 2117 |
距CBD距离 | 从TPU地理中心到CBD的距离 (m) | 11809 | 8402 |
邻近中心性(搜索半径800 m) | 空间句法中用来表征可达性,公式 | 588 | 182 |
中介中心性(搜索半径800 m) | 空间句法中用来表征可达性,公式 | 141 | 210 |
步行通勤通学变量(因变量) | |||
职员步行通勤百分比 | 职员中步行通勤的人数占该TPU中全部职员的百分比 | 0.092 | 0.077 |
学生步行通学百分比 | 学生中步行通学的人数占该TPU中全部学生的百分比 | 0.214 | 0.144 |
表2
线性回归结果"
变量 | 职员 | 学生 | ||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
基础模型1 (M1) | 扩展模型2 (M2) | 扩展模型3 (M3) | 基础模型4 (M4) | 扩展模型5 (M5) | 扩展模型6 (M6) | |||||||||||||
系数 | t值 | 系数 | t值 | 系数 | t值 | 系数 | t值 | 系数 | t值 | 系数 | t值 | |||||||
女性百分比 | -0.227* | -1.714 | 0.034 | 0.319 | 0.0003 | 0.003 | 0.001 | 0.003 | 0.058 | 0.279 | -0.072 | -0.353 | ||||||
平均年龄 | 0.001 | 0.9402 | 0.001 | 0.716 | 0.0002 | 0.183 | 0.006** | 2.060 | 0.005** | 2.265 | 0.005** | 2.535 | ||||||
平均家庭收入 | 5.466E-07** | 3.232 | 6.580E-08 | 0.466 | -1.757E-07 | -1.153 | -9.652E-07** | -2.471 | -1.039E-06** | -3.944 | -5.989E-07* | -1.966 | ||||||
平均家庭规模 | -0.141** | -10.294 | -0.074** | -5.960 | -0.048** | -3.909 | -0.068** | -2.159 | -0.066** | -3.075 | -0.049** | -2.084 | ||||||
TPU内部通勤通学占比 | 0.429** | 10.949 | 0.367** | 9.398 | 0.456** | 15.633 | 0.395** | 11.504 | ||||||||||
人口密度 | -2.592E-07* | -1.963 | 7.046E-07** | 2.547 | ||||||||||||||
容积率 | 0.011** | 3.280 | -0.011 | -1.627 | ||||||||||||||
土地利用混合度 | -0.011 | -1.056 | 0.053** | 2.318 | ||||||||||||||
道路交叉口密度 | 0.0001** | 3.251 | 0.0002** | 2.445 | ||||||||||||||
距最近地铁站距离 | 2.990E-06* | 1.709 | 8.052E-06** | 2.299 | ||||||||||||||
距CBD距离 | -5.010E-07 | -0.919 | 2.212E-06** | 2.063 | ||||||||||||||
邻近中心性(搜索半径 800 m) | -6.852E-06 | -0.385 | -8.727E-05** | -2.376 | ||||||||||||||
常数 | 0.559** | 6.901 | 0.185** | 2.540 | 0.155** | 2.027 | 0.188 | 1.006 | 0.010 | 0.081 | -0.014 | -0.103 | ||||||
R2 | 0.444 | 0.651 | 0.717 | 0.148 | 0.615 | 0.666 |
表4
空间相关性检验结果"
检验 | 职员 | 学生 | |||||
---|---|---|---|---|---|---|---|
mi/df | 统计值 | P | mi/df | 统计值 | P | ||
Moran's I (误差) | 0.2418 | 6.1754 | <0.00001 | 0.1100 | 2.8830 | 0.00394 | |
拉格朗日乘数 (滞后) | 1 | 42.2045 | <0.00001 | 1 | 9.8972 | 0.00166 | |
稳健性拉格朗日乘数 (滞后) | 1 | 19.1230 | 0.00001 | 1 | 4.8873 | 0.02705 | |
拉格朗日乘数 (误差) | 1 | 33.1992 | <0.00001 | 1 | 6.6945 | 0.00967 | |
稳健性拉格朗日乘数 (误差) | 1 | 10.1177 | 0.00147 | 1 | 1.6846 | 0.19431 | |
拉格朗日乘数 (萨玛检验) | 2 | 52.3222 | <0.00001 | 2 | 11.5819 | 0.00306 |
表5
空间计量模型分析结果"
变量 | 职员 | 学生 | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
SLM (M7) | SEM (M8) | SLM (M9) | SEM (M10) | ||||||||
系数 | z值 | 系数 | z值 | 系数 | z值 | 系数 | z值 | ||||
女性百分比 | -0.096 | -1.042 | -0.057 | -0.643 | -0.133 | -0.682 | -0.175 | -0.909 | |||
平均年龄 | 0.001 | 1.346 | 0.001 | 1.578 | 0.005** | 2.544 | 0.005** | 2.858 | |||
平均家庭收入 | -2.763E-07** | -2.069 | -1.027E-07 | -0.747 | -6.053E-07** | -2.144 | -5.067E-07* | -1.748 | |||
平均家庭规模 | -0.024** | -2.155 | -0.026** | -2.319 | -0.036 | -1.624 | -0.037 | -1.626 | |||
在TPU内部通勤通学的百分比 | 0.335** | 9.689 | 0.395** | 10.876 | 0.389** | 12.167 | 0.390** | 12.208 | |||
人口密度 | -2.374E-07** | -2.087 | -2.011E-07* | -1.744 | 5.693E-07** | 2.191 | 6.290e-07** | 2.422 | |||
容积率 | 0.010** | 3.389 | 0.009** | 3.003 | -0.008 | -1.324 | -0.003 | -0.449 | |||
土地利用混合度 | -0.005 | -0.505 | -0.012 | -1.289 | 0.056** | 2.671 | 0.050** | 2.441 | |||
道路交叉口密度 | 0.0001** | 2.392 | 0.0001** | 2.540 | 0.0001* | 1.898 | 0.0001 | 1.773 | |||
距最近地铁站距离 | -2.600E-07 | -0.145 | -1.574E-06 | -0.881 | 3.012E-06 | 0.769 | 2.236E-06 | 0.573 | |||
距CBD距离 | 6.147E-07 | 1.254 | 5.371E-07 | 1.098 | 3.588E-06** | 3.435 | 2.863E-06** | 2.753 | |||
邻近中心性(搜索半径800 m) | 1.768E-05 | 0.999 | 1.694E-05 | 0.969 | -4.826E-05 | -1.233 | -4.724E-05 | -1.216 | |||
常数 | 0.073 | 1.098 | 0.044 | 0.659 | -0.047 | -0.369 | -0.031 | -0.231 | |||
ρ (空间相关或依赖系数) | 0.263** | 5.660 | 0.543** | 7.065 | 0.158** | 3.239 | 0.366** | 3.829 | |||
R2 | 0.771 | 0.778 | 0.687 | 0.691 | |||||||
Log likelihood | 386.963 | 385.323 | 227.832 | 227.374 | |||||||
AIC | -745.927 | -744.646 | -427.664 | -428.748 |
[1] | 古杰, 周素红, 闫小培. 2014. 生命历程视角下广州市居民日常出行的时空路径分析[J]. 人文地理, 29(3): 56-62. |
[Gu J, Zhou S H, Yan X P.2014. The space-time paths of residents' daily travel in Guangzhou from a perspective of life course. Human Geography, 29(3): 56-62. ] | |
[2] | 何嘉明, 周素红, 谢雪梅. 2017. 女性主义地理学视角下的广州女性居民日常出行目的及影响因素[J]. 地理研究, 36(6): 1053-1064. |
[He J M, Zhou S H, Xie X M.2017. Female residents’ daily travel purpose and its influencing factors from the perspective of feminism: A case study in Guangzhou, China. Geographical Research, 36(6): 1053-1064. ] | |
[3] | 何舟, 宋杰洁, 孙斌栋. 2014. 城市通勤时耗的空间结构影响因素: 基于文献的研究与启示[J]. 城市规划学刊, 57(1): 65-70. |
[He Z, Song J J, Sun B D.2014. Impacts of urban spatial structure on urban commuting duration: Based on literature review. Urban Planning Forum, 57(1): 65-70. ] | |
[4] | 齐兰兰, 周素红. 2017. 广州不同阶层城市居民日常家外休闲行为时空间特征[J]. 地域研究与开发, 35(5): 57-63. |
[Qi L L, Zhou S H.2017. Spatial and temporal characteristics of city residents daily leisure behavior outside the home under view of stratum in Guangzhou City. Areal Research and Development, 35(5): 57-63. ] | |
[5] | 孙斌栋, 但波. 2015. 上海城市建成环境对居民通勤方式选择的影响[J]. 地理学报, 70(10): 1664-1674. |
[Sun B D, Dan B.2015. Impact of urban built environment on residential choice of commuting mode in Shanghai. Acta Geographica Sinica, 70(10): 1664-1674. ] | |
[6] | 孙斌栋, 何舟, 李南菲, 等. 2017. 职住均衡能够缓解交通拥堵吗? 基于GIS缓冲区方法的上海实证研究[J]. 城市规划学刊, 60(5): 98-104. |
[Sun B D, He Z, Li N F, et al.2017. Could jobs-housing balance relieve traffic congestion? A case study of Shanghai based on GIS buffer. Urban Planning Review, 60(5): 98-104. ] | |
[7] | 孙斌栋, 李南菲, 宋杰洁, 等. 2010. 职住平衡对通勤交通的影响分析: 对一个传统城市规划理念的实证检验[J]. 城市规划学刊, 43(6): 55-60. |
[Sun B D, Li N F, Song J J, et al.2010. Analysis of the impact of occupational-residential balance on commuting traffic: An empirical test of a traditional urban planning concept. Urban Planning Review, 43(6): 55-60. ] | |
[8] | 孙斌栋, 潘鑫. 2008. 城市空间结构对交通出行影响研究的进展: 单中心与多中心的论争[J]. 城市问题, 26(1): 19-22. |
[Sun B D, Pan X.2008. Progress in research on the impact of urban spatial structure on travel: Debate between single center and multi-center pattern. Urban Questions, 26(1): 19-22. ] | |
[9] | 杨林川, 张衔春, 洪世键, 等. 2016. 公共服务设施步行可达性对住宅价格的影响: 基于累积机会的可达性度量方法[J]. 南方经济, 34(1): 57-70. |
[Yang L C, Zhang X C, Hong S J, et al.2016. The impact of walking accessibility of public services on housing prices: Based on the cumulative opportunities measure. South China Journal of Economics, 34(1): 57-70. ] | |
[10] | 赵莹, 柴彦威, 关美宝. 2014. 中美城市居民出行行为的比较: 以北京市与芝加哥市为例[J]. 地理研究, 33(12): 2275-2285. |
[Zhao Y, Chai Y W, Kwan M P.2014. Comparison of urban residents’ travel behavior in China and the U S: A case study between Beijing and Chicago. Geographical Research, 33(12): 2275-2285. ] | |
[11] | 周垠, 李果. 2018. 15分钟步行圈生活便利指数评价与区县比较: 以成都市中心城区为例[J]. 上海城市规划, 27(5): 78-82. |
[Zhou Y, Li G.2018. Evaluation and district comparison of life convenience index in 15-minute walking circle: A case study of Chengdu central city. Shanghai Urban Planning Review, 27(5): 78-82. ] | |
[12] |
Adlakha D, Hipp J A, Sallis J F, et al.2018. Exploring neighborhood environments and active commuting in Chennai, India[J]. International Journal of Environment Research and Public Health, 15(9): 1840. doi: 10.3390/ijerph15091840.
doi: 10.3390/ijerph15091840 |
[13] |
Bauman A E, Reis R S, Sallis J F, et al.2012. Correlates of physical activity: Why are some people physically active and others not?[J]. The Lancet, 380: 258-271.
doi: 10.1016/S0140-6736(12)60735-1 |
[14] |
Boone-Heinonen J, Gordon-Larsen P, Guilkey D K, et al.2011. Environment and physical activity dynamics: The role of residential self-selection[J]. Psychology of Sport and Exercise, 12(1): 54-60.
doi: 10.1016/j.psychsport.2009.09.003 |
[15] | Carr L J, Dunsiger S I, Marcus B H.2010a. Validation of walk score for estimating access to walkable amenities[J]. British Journal of Sports Medicine, 45(14): 1144-1148. |
[16] |
Carr L J, Dunsiger S I, Marcus B H.2010b. Walk score™ as a global estimate of neighborhood walkability[J]. American Journal of Preventive Medicine, 39(5): 460-463.
doi: 10.1016/j.amepre.2010.07.007 |
[17] | Cervero R.1989. Land-use mixing and suburban mobility[J]. Transportation Quarterly, 42(3): 429-446. |
[18] |
Cervero R, Kockelman K.1997. Travel demand and the 3Ds: Density, diversity, and design[J]. Transportation Research Part D: Transport and Environment, 2(3): 199-219.
doi: 10.1016/S1361-9209(97)00009-6 |
[19] |
Cervero R, Sarmiento O L, Jacoby E, et al.2009. Influences of built environments on walking and cycling: Lessons from Bogotá[J]. International Journal of Sustainable Transportation, 3(4): 203-226.
doi: 10.1080/15568310802178314 |
[20] |
Duncan M J, Winkler E, Sugiyama T, et al.2010. Relationships of land use mix with walking for transport: Do land uses and geographical scale matter?[J]. Journal of Urban Health, 87(5): 782-795.
doi: 10.1007/s11524-010-9488-7 |
[21] |
Ewing R, Cervero R.2010. Travel and the built environment: A meta-analysis[J]. Journal of the American Planning Association, 76(3): 265-294.
doi: 10.1080/01944361003766766 |
[22] |
Forsyth A, Oakes J M, Lee B, et al.2009. The built environment, walking, and physical activity: Is the environment more important to some people than others?[J]. Transportation Research Part D: Transport and Environment, 14(1): 42-49.
doi: 10.1016/j.trd.2008.10.003 |
[23] |
Forsyth A, Oakes J M, Schmitz K H, et al.2007. Does residential density increase walking and other physical activity?[J]. Urban Studies, 44(4): 679-697.
doi: 10.1080/00420980601184729 |
[24] |
Handy S, Cao X, Mokhtarian P L.2006. Self-selection in the relationship between the built environment and walking: Empirical evidence from Northern California[J]. Journal of the American Planning Association, 72(1): 55-74.
doi: 10.1080/01944360608976724 |
[25] |
Heath G W, Parra D C, Sarmiento O L, et al.2012. Evidence-based intervention in physical activity: Lessons from around the world[J]. The Lancet, 380: 272-281.
doi: 10.1016/S0140-6736(12)60816-2 |
[26] | Lee I-M, Buchner D M.2008. The importance of walking to public health[J]. Medicine and Science in Sports and Exercise, 40(S7), doi: 10.1249/MSS.0b013e31817c65d0. |
[27] | Lu W, McKyer E L J, Lee C, et al.2014. Perceived barriers to children’s active commuting to school: A systematic review of empirical, methodological and theoretical evidence[J]. International Journal of Behavioral Nutrition and Physical Activity, 11(1), doi: 10.1186/s12966-014-0140-x. |
[28] | Lu Y, Sun G, Sarkar C, et al.2018. Commuting mode choice in a high-density city: Do land-use density and diversity matter in Hong Kong?[J]. International Journal of Environmental Research and Public Health, 15(5), doi: 10.3390/ijerph15050920. |
[29] |
Lu Y, Xiao Y, Ye Y.2017. Urban density, diversity and design: Is more always better for walking? A study from Hong Kong[J]. Preventive Medicine, 103: S99-S103.
doi: 10.1016/j.ypmed.2016.08.042 |
[30] |
Nagel C L, Carlson N E, Bosworth M, et al.2008. The relation between neighborhood built environment and walking activity among older adults[J]. American Journal of Epidemiology, 168(4): 461-468.
doi: 10.1093/aje/kwn158 |
[31] | Oakes J M, Forsyth A, Schmitz K H.2007. The effects of neighborhood density and street connectivity on walking behavior: The Twin Cities walking study[J]. Epidemiologic Perspectives & Innovations, 4(1), doi: 10.1186/1742-5573-4-16. |
[32] |
Pratt M, Sarmiento O L, Montes F, et al.2012. The implications of megatrends in information and communication technology and transportation for changes in global physical activity[J]. The Lancet, 380: 282-293.
doi: 10.1016/S0140-6736(12)60736-3 |
[33] | Sun G, Oreskovic N M, Lin H.2014. How do changes to the built environment influence walking behaviors? A longitudinal study within a university campus in Hong Kong[J]. International Journal of Health Geographics, 13(1), doi: 10.1186/1476-072X-13-28. |
[34] |
Vale D S, Pereira M.2016. Influence on pedestrian commuting behavior of the built environment surrounding destinations: A structural equations modeling approach[J]. International Journal of Sustainable Transportation, 10(8): 730-741.
doi: 10.1080/15568318.2016.1144836 |
[35] |
Wankel L M, Berger B G.1990. The psychological and social benefits of sport and physical activity[J]. Journal of Leisure Research, 22(2): 167-182.
doi: 10.1080/00222216.1990.11969823 |
[36] |
Yang L C, Wang B, Zhou J P, et al.2018. Walking accessibility and property prices[J]. Transportation Research Part D: Transport and Environment, 62: 551-562.
doi: 10.1016/j.trd.2018.04.001 |
[37] | Yang L C, Wang X, Sun G B, et al.2019. Modeling the perception of walking environmental quality in a traffic-free tourist destination[J]. Journal of Travel & Tourism Marketing, doi: 10.1080/10548408.2019.1598534. |
[38] |
Yang L C, Zhou J P, Shyr O F, et al.2019. Does bus accessibility affect property prices?[J]. Cities, 84: 56-65.
doi: 10.1016/j.cities.2018.07.005 |
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