PROGRESS IN GEOGRAPHY ›› 2021, Vol. 40 ›› Issue (12): 2048-2060.doi: 10.18306/dlkxjz.2021.12.006
• Articles • Previous Articles Next Articles
TONG Zhaomin1(), AN Rui1, LIU Yaolin1,2,3,*(
)
Received:
2021-01-18
Revised:
2021-05-25
Online:
2021-12-28
Published:
2021-12-24
Contact:
LIU Yaolin
E-mail:tongzm2215@126.com;yaolin610@163.com
Supported by:
TONG Zhaomin, AN Rui, LIU Yaolin. Impact of the built environment on residents’ commuting mode choices: A case study of urban village in Wuhan City[J].PROGRESS IN GEOGRAPHY, 2021, 40(12): 2048-2060.
Tab.1
Factors and collinearity diagnosis
指标 | 变量 | 变量解释 | VIF |
---|---|---|---|
密度 | 路网密度(km/km²) | 居民1500 m缓冲区内路网密度 | 15.387 |
居住人口密度(人/m²) | 居民1500 m缓冲区内居住人口密度 | 17.464 | |
就业人口密度(人/m²) | 居民1500 m缓冲区内就业人口密度 | 38.630 | |
早高峰人口密度(人/m²) | 居民1500 m缓冲区内上午8:00~9:00平均人口密度 | 42.854 | |
多样性 | 土地利用混合度 | 居民所在250 m格网内商服、工业用地、教育用地、公园广场、公共设施用地及住宅用地6类用地的土地利用混合熵指数: | 2.565 |
职住比 | 居民1500 m缓冲区内就业人口与居住人口比值 | 1.852 | |
设计 | 商服用地比例(%) | 居民所在250 m格网商服用地占比 | 1.740 |
工业用地比例(%) | 居民所在250 m格网工业用地占比 | 1.510 | |
居住用地比例(%) | 居民所在250 m格网居住用地占比 | 1.170 | |
交叉路口个数 | 居民1500 m缓冲区内岔路口个数 | 13.484 | |
公共交通可达性 | 到最近地铁站距离(m) | 居民到最近地铁站的欧氏距离 | 1.891 |
到最近公交站距离(m) | 居民到最近公交站的欧氏距离 | 1.610 | |
公交站点个数(个) | 居民1000 m范围内公交站个数 | 25.054 | |
目的地可达性 | 到市中心距离(m) | 居民到武汉市8个商业中心的欧氏距离,包括中南路商圈、钟家村商圈、徐东商圈、司门口商圈、江汉路、光谷、街道口、建设大道 | 2.433 |
社会经济属性 | 所在地区房价(元/m²) | 在武汉主城区范围内使用链家网爬取的房价数据进行克里金插值,将插值结果提取至居民所在地 | 1.854 |
Tab.2
Factors and sample statistics
指标 | 变量 | 平均值 | 标准差 | VIF | 预期影响 |
---|---|---|---|---|---|
密度 | 路网密度(km/km²) | 3.561 | 1.851 | 6.868 | - |
多样性 | 土地利用混合度 | 0.294 | 0.166 | 2.328 | - |
职住比 | 0.753 | 0.614 | 1.473 | - | |
设计 | 商服用地比例(%) | 1.383 | 3.217 | 1.551 | + |
工业用地比例(%) | 3.068 | 7.133 | 1.470 | - | |
居住用地比例(%) | 11.916 | 15.344 | 1.142 | - | |
交叉路口个数 | 27.689 | 18.880 | 6.575 | + | |
公共交通可达性 | 到最近地铁站距离(m) | 1963.493 | 1630.120 | 1.790 | - |
到最近公交站距离(m) | 375.802 | 323.990 | 1.240 | - | |
目的地可达性 | 到市中心距离(m) | 7583.092 | 3369.462 | 1.801 | + |
社会经济属性 | 所在地区房价(元/m²) | 12597.075 | 4361.279 | 1.142 | - |
Tab.4
Traditional binary logit model results
变量 | 标准化系数 | 标准误差 | 显著性 | 优势比 |
---|---|---|---|---|
路网密度 | -0.097 | 0.147 | 0.508 | 0.907 |
土地利用混合度 | -0.005 | 0.040 | 0.904 | 0.995 |
职住比 | -0.033 | 0.034 | 0.319 | 0.967 |
商服用地比例 | 0.017 | 0.033 | 0.609 | 1.017 |
工业用地比例 | -0.016 | 0.033 | 0.631 | 0.984 |
住宅用地比例 | -0.062 | 0.029 | 0.031 | 0.940 |
交叉路口个数 | 0.069 | 0.092 | 0.457 | 1.071 |
到最近地铁站距离 | -0.044 | 0.037 | 0.238 | 0.957 |
到最近公交站距离 | -0.149 | 0.038 | <0.001 | 0.862 |
到市中心距离 | 0.123 | 0.038 | 0.001 | 1.131 |
所在地区房价 | -0.021 | 0.120 | 0.858 | 0.979 |
[1] | 赖亚妮, 桂艺丹. 城中村土地发展问题: 文献回顾与研究展望[J]. 城市规划, 2019, 43(7):108-114. |
[ Lai Yani, Gui Yidan. Land development issues in urban villages: Literature review and research perspectives. City Planning Review, 2019, 43(7):108-114. ] | |
[2] | 卢福营. 城中村改造: 一项系统的新型城镇化工程[J]. 社会科学, 2017(10):84-89. |
[ Lu Fuying. Village-in-city reconstruction: A systematic project for new urbanization. Journal of Social Sciences, 2017(10):84-89. ] | |
[3] | 卢青青. 过渡型城中村的矛盾内部化与治理困境[J]. 江汉学术, 2020, 39(3):33-41. |
[ Lu Qingqing. Transitional urban villages' contradiction internalization and governance difficulties. Jianghan Academic, 2020, 39(3):33-41. ] | |
[4] | 战洋, 童小溪. “城中村”与中国城市化的特殊道路[J]. 清华大学学报 (哲学社会科学版), 2017, 32(6):183-189. |
[ Zhan Yang, Tong Xiaoxi. Peasant-dominated urbanization: Urban villages and the unique path of China's urbanization. Journal of Tsinghua University (Philosophy and Social Sciences), 2017, 32(6):183-189. ] | |
[5] | 文超, 杨新海, 文剑钢, 等. 基于“城市针灸”的城中村有机更新模式探究[J]. 城市发展研究, 2017, 24(11):43-50. |
[ Wen Chao, Yang Xinhai, Wen Jiangang, et al. The exploration for organic update model upon "urban acupuncture" in urban village. Urban Development Studies, 2017, 24(11):43-50. ] | |
[6] | 安黎, 冯健. “空间错配”视角下城中村流动人口职住关系研究: 以北京市挂甲屯村、皮村为例[J]. 城市发展研究, 2020, 27(12):123-131. |
[ An Li, Feng Jian. Study on the jobs-housing relationship of the transient population in urban villages from the perspective of spatial mismatch: A case study of Guajiatun and Picun, Beijing. Urban Development Studies, 2020, 27(12):123-131. ] | |
[7] |
张艳, 刘志林. 市场转型背景下北京市中低收入居民的住房机会与职住分离研究[J]. 地理科学, 2018, 38(1):11-19.
doi: 10.13249/j.cnki.sgs.2018.01.002 |
[ Zhang Yan, Liu Zhilin. Access to housings and home-work separation of moderate to low-income residents in Beijing under the market-oriented transition. Scientia Geographica Sinica, 2018, 38(1):11-19. ] | |
[8] |
张纯, 程志华, 于晓萍, 等. 乌鲁木齐公共交通基础设施对低收入群体就业的影响研究[J]. 地理科学进展, 2020, 39(1):111-119.
doi: 10.18306/dlkxjz.2020.01.011 |
[ Zhang Chun, Cheng Zhihua, Yu Xiaoping, et al. Impact of public transportation infrastructure on employment of the low-income group in Urumqi. Progress in Geography, 2020, 39(1):111-119. ] | |
[9] |
Cai M M, Jiao J F, Luo M H, et al. Identifying transit deserts for low-income commuters in Wuhan metropolitan area, China[J]. Transportation Research Part D: Transport and Environment, 2020, 82:102292. doi: 10.1016/j.trd.2020.102292.
doi: 10.1016/j.trd.2020.102292 |
[10] | Han C Y, Liu X Q, Shen X J, et al. Evaluating the spatial deprivation of public transportation resources in areas of rapid urbanization: Accessibility and social equity[J]. Discrete Dynamics in Nature and Society, 2019, 2019:1-11. |
[11] |
Ewing R, Cervero R. Travel and the built environment[J]. Journal of the American Planning Association, 2010, 76(3):265-294.
doi: 10.1080/01944361003766766 |
[12] |
Stevens M R. Does compact development make people drive less?[J]. Journal of the American Planning Association, 2017, 83(1):7-18.
doi: 10.1080/01944363.2016.1240044 |
[13] |
Sun B D, Ermagun A, Dan B. Built environmental impacts on commuting mode choice and distance: Evidence from Shanghai[J]. Transportation Research Part D: Transport and Environment, 2017, 52:441-453.
doi: 10.1016/j.trd.2016.06.001 |
[14] |
Luan X, Cheng L, Song Y, et al. Better understanding the choice of travel mode by urban residents: New insights from the catchment areas of rail transit stations[J]. Sustainable Cities and Society, 2020, 53:101968. doi: 10.1016/j.scs.2019.101968.
doi: 10.1016/j.scs.2019.101968 |
[15] |
Chen E H, Ye Z R, Wang C, et al. Discovering the spatio-temporal impacts of built environment on metro ridership using smart card data[J]. Cities, 2019, 95:102359. doi: 10.1016/j.cities.2019.05.028.
doi: 10.1016/j.cities.2019.05.028 |
[16] |
Chan K, Farber S. Factors underlying the connections between active transportation and public transit at commuter rail in the Greater Toronto and Hamilton area[J]. Transportation, 2020, 47(5):2157-2178.
doi: 10.1007/s11116-019-10006-w |
[17] |
Cao X J, Mokhtarian P L, Handy S L. Examining the impacts of residential self-selection on travel behaviour: A focus on empirical findings[J]. Transport Reviews, 2009, 29(3):359-395.
doi: 10.1080/01441640802539195 |
[18] | 张延吉, 胡思聪, 陈小辉, 等. 城市建成环境对居民通勤方式的影响: 基于福州市的经验研究[J]. 城市发展研究, 2019, 26(3):72-78. |
[ Zhang Yanji, Hu Sicong, Chen Xiaohui, et al. The impact of urban built environment on residential choice of commuting mode: Based on empirical research in Fuzhou. Urban Development Studies, 2019, 26(3):72-78. ] | |
[19] |
Pinjari A R, Pendyala R M, Bhat C R, et al. Modeling residential sorting effects to understand the impact of the built environment on commute mode choice[J]. Transportation, 2007, 34(5):557-573.
doi: 10.1007/s11116-007-9127-7 |
[20] |
van Wee B, Handy S. Key research themes on urban space, scale, and sustainable urban mobility[J]. International Journal of Sustainable Transportation, 2016, 10(1):18-24.
doi: 10.1080/15568318.2013.820998 |
[21] |
孙斌栋, 但波. 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, 2015, 70(10):1664-1674.
doi: 10.11821/dlxb201510010 |
[ Sun Bindong, Dan Bo. Impact of urban built environment on residential choice of commuting mode in Shanghai. Acta Geographica Sinica, 2015, 70(10):1664-1674. ] | |
[22] |
刘吉祥, 周江评, 肖龙珠, 等. 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.
doi: 10.18306/dlkxjz.2019.06.002 |
[ Liu Jixiang, Zhou Jiangping, Xiao Longzhu, et al. Effects of the built environment on pedestrian communing to work and school: The Hong Kong case, China. Progress in Geography, 2019, 38(6):807-817. ] | |
[23] | 吴姝悦. 基于TOD的大城市建成环境分析及公交出行行为影响研究[D]. 南京: 东南大学, 2019. |
[ Wu Shuyue. Study on large city built environment analysis and its impact on public transportation travel behavior based on TOD. Nanjing, China: Southeast University, 2019. ] | |
[24] |
Ding C, Cao X Y, Wang Y P. Synergistic effects of the built environment and commuting programs on commute mode choice[J]. Transportation Research Part A: Policy and Practice, 2018, 118:104-118.
doi: 10.1016/j.tra.2018.08.041 |
[25] |
Tao T, Wang J Y, Cao X Y. Exploring the non-linear associations between spatial attributes and walking distance to transit[J]. Journal of Transport Geography, 2020, 82:102560. doi: 10.1016/j.jtrangeo.2019.102560.
doi: 10.1016/j.jtrangeo.2019.102560 |
[26] |
Cheng L, De Vos J, Zhao P J, et al. Examining non-linear built environment effects on elderly's walking: A random forest approach[J]. Transportation Research Part D: Transport and Environment, 2020, 88:102552. doi: 10.1016/j.trd.2020.102552.
doi: 10.1016/j.trd.2020.102552 |
[27] |
Ding C, Cao X Y, Liu C. How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds[J]. Journal of Transport Geography, 2019, 77:70-78.
doi: 10.1016/j.jtrangeo.2019.04.011 |
[28] |
Gan Z X, Yang M, Feng T, et al. Examining the relationship between built environment and metro ridership at station-to-station level[J]. Transportation Research Part D: Transport and Environment, 2020, 82:102332. doi: 10.1016/j.trd.2020.102332.
doi: 10.1016/j.trd.2020.102332 |
[29] |
Galster G C. Nonlinear and threshold effects related to neighborhood: Implications for planning and policy[J]. Journal of Planning Literature, 2018, 33(4):492-508.
doi: 10.1177/0885412218793693 |
[30] | 仝德, 高静, 龚咏喜. 城中村对深圳市职住空间融合的影响: 基于手机信令数据的研究[J]. 北京大学学报 (自然科学版), 2020, 56(6):1091-1101. |
[ Tong De, Gao Jing, Gong Yongxi. Impact of urban village on job-housing balance in Shenzhen: A study using mobile phone signaling data. Acta Scientiarum Naturalium Universitatis Pekinensis, 2020, 56(6):1091-1101. ] | |
[31] | 刘耀林, 陈龙, 安子豪, 等. 基于公交刷卡数据的武汉市职住通勤特征研究[J]. 经济地理, 2019, 39(2):93-102. |
[ Liu Yaolin, Chen Long, An Zihao, et al. Research on job-housing and commuting in Wuhan based on bus smart card data. Economic Geography, 2019, 39(2):93-102. ] | |
[32] |
段亚明, 刘勇, 刘秀华, 等. 基于宜出行大数据的多中心空间结构分析: 以重庆主城区为例[J]. 地理科学进展, 2019, 38(12):1957-1967.
doi: 10.18306/dlkxjz.2019.12.011 |
[ Duan Yaming, Liu Yong, Liu Xiuhua, et al. Measuring polycentric urban structure using Easygo big data: A case study of Chongqing metropolitan area. Progress in Geography, 2019, 38(12):1957-1967. ] | |
[33] |
Yang J W, Su P R, Cao J. On the importance of Shenzhen metro transit to land development and threshold effect[J]. Transport Policy, 2020, 99:1-11.
doi: 10.1016/j.tranpol.2020.08.014 |
[34] |
杨文越, 曹小曙. 居住自选择视角下的广州出行碳排放影响机理[J]. 地理学报, 2018, 73(2):346-361.
doi: 10.11821/dlxb201802010 |
[ Yang Wenyue, Cao Xiaoshu. The influence mechanism of travel-related CO2 emissions from the perspective of residential self-selection: A case study of Guangzhou. Acta Geographica Sinica, 2018, 73(2):346-361. ] | |
[35] | Cao J. Residential self-selection in the relationships between the built environment and travel behavior: Introduction to the special issue[J]. Journal of Transport and Land Use, 2014, 7(3):1-3. |
[36] |
Wang D G, Lin T. Residential self-selection, built environment, and travel behavior in the Chinese context[J]. Journal of Transport and Land Use, 2014, 7(3):5-14.
doi: 10.5198/jtlu.v7i3 |
[37] |
Zhao P J. The impact of the built environment on individual workers' commuting behavior in Beijing[J]. International Journal of Sustainable Transportation, 2013, 7(5):389-415.
doi: 10.1080/15568318.2012.692173 |
[38] |
Yu L, Xie B L, Chan E H W. Exploring impacts of the built environment on transit travel: Distance, time and mode choice, for urban villages in Shenzhen, China[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 132:57-71.
doi: 10.1016/j.tre.2019.11.004 |
[39] | 席东其. 基于多源大数据的城市交通可达性与公平性评价: 以昆山市为例[D]. 南京: 南京大学, 2020. |
[ Xi Dongqi. Evaluation of urban traffic accessibility and equity based on multi-source big data: A case study of Kunshan. Nanjing, China: Nanjing University, 2020. ] | |
[40] | 郑红玉. 土地混合利用多尺度测度的理论和方法研究: 以上海市为例[D]. 杭州: 浙江大学, 2018. |
[ Zheng Hongyu. Theory and method for multi-scale measurement of mixed land use: A case study of Shanghai. Hangzhou, China: Zhejiang University, 2018. ] | |
[41] | 黄金侠. 基于多源数据的长沙市人口多尺度空间化建模[D]. 长沙: 湖南师范大学, 2020. |
[ Huang Jinxia. Multi-scale modeling of population spatialization in Changsha based on multi-source data. Changsha, China: Hunan Normal University, 2020. ] | |
[42] | 毛亚萍, 房世峰. 基于机器学习的参考作物蒸散量估算研究[J]. 地球信息科学学报, 2020, 22(8):1692-1701. |
[ Mao Yaping, Fang Shifeng. Research of reference evapotranspiration's simulation based on machine learning. Journal of Geo-information Science, 2020, 22(8):1692-1701. ] | |
[43] |
Elith J, Leathwick J R, Hastie T. A working guide to boosted regression trees[J]. Journal of Animal Ecology, 2008, 77(4):802-813.
doi: 10.1111/j.1365-2656.2008.01390.x pmid: 18397250 |
[44] |
Friedman J H. Greedy function approximation: A gradient boosting machine[J]. The Annals of Statistics, 2001, 29(5):1189-1232.
doi: 10.1214/aos/1013203450 |
[45] |
Chung Y S. Factor complexity of crash occurrence: An empirical demonstration using boosted regression trees[J]. Accident Analysis & Prevention, 2013, 61:107-118.
doi: 10.1016/j.aap.2012.08.015 |
[46] |
Zhang M. The role of land use in travel mode choice: Evidence from Boston and Hong Kong[J]. Journal of the American Planning Association, 2004, 70(3):344-360.
doi: 10.1080/01944360408976383 |
[47] |
Kamruzzaman M, Washington S, Baker D, et al. Built environment impacts on walking for transport in Brisbane, Australia[J]. Transportation, 2016, 43(1):53-77.
doi: 10.1007/s11116-014-9563-0 |
[48] |
van Acker V, Witlox F. Commuting trips within tours: How is commuting related to land use?[J]. Transportation, 2011, 38(3):465-486.
doi: 10.1007/s11116-010-9309-6 |
[49] | 赵鹏军, 李南慧, 李圣晓. TOD建成环境特征对居民活动与出行影响: 以北京为例[J]. 城市发展研究, 2016, 23(6):45-51. |
[ Zhao Pengjun, Li Nanhui, Li Shengxiao. The impacts of the built environment on residents' acitivities and travel behavior in TOD areas: A case study of Beijing. Urban Development Studies, 2016, 23(6):45-51. ] | |
[50] |
El-Geneidy A, Grimsrud M, Wasfi R, et al. New evidence on walking distances to transit stops: Identifying redundancies and gaps using variable service areas[J]. Transportation, 2014, 41(1):193-210.
doi: 10.1007/s11116-013-9508-z |
[51] |
Chen C, Gong H M, Paaswell R. Role of the built environment on mode choice decisions: Additional evidence on the impact of density[J]. Transportation, 2008, 35(3):285-299.
doi: 10.1007/s11116-007-9153-5 |
[52] |
Bin O, Polasky S. Effects of flood hazards on property values: Evidence before and after hurricane Floyd[J]. Land Economics, 2004, 80(4):490-500.
doi: 10.2307/3655805 |
[53] | 吴静娴, 胡荣, 赵靖, 等. 基于多源数据的迁居个体通勤方式选择研究[J]. 武汉理工大学学报 (交通科学与工程版), 2020, 44(6):984-988. |
[ Wu Jingxian, Hu Rong, Zhao Jing, et al. An investigation on commute mode choice of relocated residents based on multi-source data. Journal of Wuhan University of Technology (Transportation Science & Engineering), 2020, 44(6):984-988. ] | |
[54] |
Ivan I, Horák J, Zajíčková L, et al. Factors influencing walking distance to the preferred public transport stop in selected urban centres of Czechia[J]. GeoScape, 2019, 13(1):16-30.
doi: 10.2478/geosc-2019-0002 |
[55] |
Gutiérrez J, García-Palomares J C. Distance-measure impacts on the calculation of transport service areas using GIS[J]. Environment and Planning B: Planning and Design, 2008, 35(3):480-503.
doi: 10.1068/b33043 |
[1] | SHEN Jie, ZHANG Keyun. An empirical analysis of factors leading to typical urban problems in China [J]. PROGRESS IN GEOGRAPHY, 2020, 39(1): 1-12. |
[2] | Wensheng LIN, Jian FENG, Ye LI. Influence of ICT on housing and employment related migration space of residents in urban villages: A case study of five urban villages in Beijing [J]. PROGRESS IN GEOGRAPHY, 2018, 37(2): 276-286. |
[3] | Xiaojie WEN, Shunbo YAO, Minjuan ZHAO. Coordinating the development of urbanization and vegetation coverage based on precipitation [J]. PROGRESS IN GEOGRAPHY, 2018, 37(10): 1352-1361. |
[4] | Chengzhi ZHENG, Wangfeng ZHANG, Bingyan WU, Bo LIANG. Job-housing mismatch of floating population in urban villages of Beijing [J]. PROGRESS IN GEOGRAPHY, 2017, 36(4): 416-425. |
|