Factors Influencing Walking Distance to the Preferred Public Transport Stop in selected urban centres of Czechia

Igor Ivan 1 , Jiří Horák 1 , Lenka Zajíčková 2 , Jaroslav Burian 2 ,  and David Fojtík 3
  • 1 Department of Geoinformatics, Faculty of Mining and Geology, VSB-Technical University of Ostrava, Ostrava, Czechia
  • 2 Department of Geoinformatics, Palacký University Olomouc, Olomouc, Czechia
  • 3 Department of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, Ostrava, Czechia


One of the ways of improving the attractiveness of public transport is to bring it closer to its potential users. A long walking distance from a stop is often one of the critical factors limiting its more frequent and extensive use. Studies dealing with the accessibility of transport networks usually work only with the closest stop. This article analyses the actual walking distance from the place of residence to the preferred stop. The survey used a questionnaire method and was conducted in two cities in the Czech Republic—Ostrava and Olomouc. Based on the results of the study, the average walking distance was assessed and the impact of demographic characteristics (gender, age, education, number of members in the household, economic activity, the presence of a child in the household, and car ownership), transport behavior (preferred mode of transportation, car convenience and opinions on public transport), and urban characteristics (prevailing housing type) on the walking distance were analyzed. The main findings prove a significant impact on walking distance by a number of these factors, but the preferred use of a car for commuting or unemployment does not significantly affect walking distance.

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  • Adams EJ, Esliger DW, Taylor IM, Sherar LB (2017) Individual, employment and psychosocial factors influencing walking to work: Implications for intervention design. PLoS ONE 12(2).

  • Ayvalik CK, Khisty CJ (2002) Heuristic analysis of impacts of commuter rail station consolidation on pedestrian access. Transportation Research Record 1793: 47–54.

  • Bernard HR (2012) Social Research Methods: Qualitative and Quantitative Approaches. SAGE Publications, London.

  • Biba S, Curtin SK, Manca G (2010) A new method for determining the population with walking access to transit. International Journal of Geographical Information Science 24(3): 347–364.

  • Bilková K, Križan F, Horňák M, Barlík P, Kita P (2017) Comparing two distance measures in the spatial mapping of food deserts: The case of Petržalka, Slovakia. Moravian Geographical Reports 25(2): 95–103.

  • Burian J, Brus J, Voženílek V (2013) Development of Olomouc City in 1930–2009: based on analysis of functional areas. Journal of Maps 9(1): 64–67.

  • Burian J, Brychtová A, Vávra A (2015) Analytical material for planning in Olomouc, Czech Republic. Journal of Maps 12(4): 649–654.

  • Burian J, Zajíčková L, Ivan I, Macků K (2018) Attitudes and motivation to use public or individual transport: a case study of two middle-sized cities. Social Sciences 7(6): 1–25.

  • Currie G (2010) Quantifying spatial gaps in public transport supply based on social needs. Journal of Transport Geography 18(1): 31–41.

  • Čekal J (2006) Jihočeský kraj: regionálně geografická analýza prostorové mobility obyvatelstva. Brno: Regionální geografie a regionální rozvoj, Masarykova univerzita. Ph.D. Theses.

  • Daniels R, Mulley C (2013) Explaining walking distance to public transport: the dominance of public transport supply. The Journal of Transport and Land Use 6(2): 5–20.

  • Dill J (2003) Transit use and proximity to rail: results from large employment sites in the San Francisco, California, Bay area. Transportation Research Record 1835: 19–24.

  • Ďurček P, Horňák M (2016) Population potential within the urban environment and intra-urban railway network opportunities in Bratislava (Slovakia). Moravian Geographical Reports 24(4): 52–64.

  • El-Geneidy A, Grimsrud M, Wasfi R, Tétreault P, Surprenant-Legault J (2014) New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas. Transportation 41(1): 193–210.

  • El-Geneidy AM, Tétreault PR, Surprenant-Legault J (2009) Pedestrian access to transit: identifying redundancies and gaps using a variable service area analysis. Transportation Research Board 89th Annual Meeting.

  • Fotheringham AS, Wong DW (1991) The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning A 23(7): 1025–1044.

  • Fransen K, Neutens T, Farber S, De Maeyer P, Deruyter G, Witlox F (2015) Identifying public transport gaps using time-dependent accessibility levels. Journal of Transport Geography 48: 176–187.

  • Furth PG, Mekuria MC, Sanclemente JL (2007) Stop spacing analysis using geographic information system tools with parcel and street network data. Transportation Research Record 2034: 73–81.

  • García-Palomares JC, Gutiérrez J (2013) Walking accessibility to public transport: an analysis based on microdata and GIS. Environment and Planning B: Planning and Design 40(6): 1087–1102.

  • Gutiérrez J, García-Palomares JC (2008) Distance-measure impacts on the calculation of transport service areas using GIS. Environment and Planning B: Planning and Design 35(3): 480–503.

  • Hernández D, Witter R (2015) Perceived vs. actual distance to transit in Santiago, Chile. Journal of Public Transportation 18(4): 16–30.

  • Hruška-Tvrdý L, Kukuliac P, Horák J, Ivan I, Foldynová I (2012) Socioeconomic atlas of Ostrava. In: Klímová V, Zítek V (eds) 15th International Colloquium on Regional Sciences. Masaryk University, pp. 181–192.

  • Hsiao S, Lu J, Sterling J, Weatherford M (1997) Use of geographic information system for analysis of transit pedestrian access. Transportation Research Record 1604: 50–59.

  • Hyvnar V, Rohrerová L et al. (2016): Limits of land use. Institute for Spatial Development. <http://www.uur.cz/default.asp?ID=2591>

  • Ivan I (2010) Docházka na zastávku a její vliv na dojížďku do zaměstnání. Geografie 115(4): 393–412.

  • Kimpel, T., Dueker, K., El-Geneidy, A. (2007): Using GIS to measure the effect of overlapping service areas on passenger boardings at bus stops. URISA Journal 19: 5–11.

  • Kozel P, Orlíková L, Michalcová S (2018) The modified rural postman problem in vehicle route optimization. Communications - Scientific Letters of the University of Zilina 20(3): 88–92.

  • Kraft S (2011) Aktuální změny v dopravním systému České republiky: geografická analýza. Brno, Ph.D. Theses.

  • Kraft S (2016) Measuring and modelling the spatial accessibility of public transport stops in GIS. Hungarian Geographical Bulletin 65(1): 57–69.

  • Langford M, Fry R, Higgs G (2012) Measuring transit system accessibility using a modified two-step floating catchment technique. International Journal of Geographical Information Science 26(2): 193–214.

  • Laverty AA, Mindell JS, Webb EA, Millett C (2013) Active travel to work and cardiovascular risk factors in the United Kingdom. American Journal of Preventive Medicine 45(3): 282–288.

  • Loutzenheiser D (1997) Pedestrian access to transit: Modeling of walk trips and their design and urban form determination around bay area rapid transit stations. Transportation Research Record 1604: 40–49.

  • L’uptak V, Gasparik J, Chovancová M (2017) Proposal for evaluating a connection quality within transport networks. In: Proceedings of the 18th International Scientific Conference on LOGI Location: Ceske Budejovice. MATEC Web of Conferences, Vol. 134, Article 00033. MATEC Web of Conferences 134, 00033.

  • Mavoa S, Witten K, McCreanor T, O’Sullivan D (2012) GIS based destination accessibility via public transit and walking in Auckland, New Zealand. Journal of Transport Geography 20: 15–22.

  • MD (2014) Transport Yearbook – Czech Republic, 2014. Ministry of Transport.

  • Olivková I (2015) Model for measuring passenger satisfaction and assessing mass transit quality. Journal of Public Transportation 18(3): 52–70.

  • O’Neill WA, Ramsey RD, Chou J (1992) Analysis of transit service areas using geographic information systems. Transportation Research Record 1364: 131–138.

  • Peng A, Dueker K, Strathman J, Hopper J (1997) A simultaneous route level transit patronage model: demand, supply and inter-route relationship. Transportation Research Record 24: 159–181.

  • Pucher J (1999) The transformation of urban transport in the Czech Republic, 1988–1998. Transport Policy 6(4): 225–236.

  • Seidenglanz D (2007) Dopravní charakteristiky venkovského prostoru. Brno, Katedra Regionální geografie a regionálního rozvoje PřF Masarykovy univerzity. Ph.D. Theses.

  • Van Wee B, Geurs K, Chorus C (2013) Information, communication, travel behavior and accessibility. The Journal of Transport and Land Use 6(3): 1–16.

  • Van Wee B (2016) Accessible accessibility research challenges. Journal of Transport Geography 51: 9–16.

  • Whyte WH (2012) City: rediscovering the center. University of Pennsylvania Press.

  • Witlox F (2015) Beyond the data smog? Transportation Revue 35(3): 245–249.

  • Wu BM, Hine JP (2003) A PTAL approach to measuring changes in bus service accessibility. Transport Policy 10(4): 307–320.

  • Yigitcanlar T, Sipe NG, Evans R, Pitot M (2007) A GIS-based land use and public transport accessibility indexing model. Australian Planner 44(3): 30–37.

  • Zajíčková L (2012) Časové variace dojížďky do města Olomouc prostředky hromadné dopravy osob. Olomouc. Univerzita Palackého v Olomouci. Diploma Thesis.

  • Zhao F, Chow L-F, Li M-T, Gan A, Ubaka I (2003) Forecasting transit walk accessibility – regression model alternative to buffer method. Transportation Research Record 1835: 34–41.


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