A Markovian measure for evaluating accessibility to urban opportunities

Alireza Sahebgharani, Hossein Haghshenas, Mahmoud Mohammadi


Accessibility is a fundamental notion in urban planning and its related fields. While accessibility is dynamic and varies during different time moments, most of the accessibility metrics are static and do not take this variation into account. In doing so, to address the questions of (1) how accessible urban opportunities are in different time moments and (2) how accessibility value of a person to a certain place changes regarding his/her spatiotemporal restrictions in time instants, this article—by using semi-Markovian and Brownian Bridge stochastic processes—offers a probabilistic time-dependent accessibility model that blends the magnitude of opportunities magnitude with the probability of individuals visiting.

To show the model’s applicability, it was applied on a hypothetical case, along with two common accessibility metrics, and the outputs were compared. Then the proposed model was implemented in a study area for measuring temporal accessibility in two real policies made for daily markets in Isfahan, Iran. The first policy that presented the model application for analytical purposes was “market exclusion and area expansion,” and the second policy that depicted the model implementation for normative usage was “new market location.”

Results of the model execution on the hypothetical cases indicated there was a significant difference between the outputs of the common metrics and the ones of the proposed model. In addition, in the study area, the first policy generated higher total accessibility value in comparison with the second policy when market 2 was excluded and the area for market 8 was doubled.


accessibility; time geography; visiting probability; space-time prism

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Banister, D. (2008). The sustainable mobility paradigm. Transport Policy, 15(2), 73–80.

Bazzano, L. A., He, J., Ogden, L. G., Loria, C. M., Vupputuri, S., Myers, L., & Whelton, P. K. (2002). Fruit and vegetable intake and risk of cardiovascular disease in US adults: The first national health and nutrition examination survey epidemiologic follow-up study. The American Journal of Clinical Nutrition, 76(1), 93–99.

Breheny, M. J. (1978). The measurement of spatial opportunity in strategic planning. Regional Studies, 12(4), 463–479.

Burns, L. D. (1979). Transportation, temporal, and spatial components of accessibility. Geographical Analysis 13(2), 185_187. https://doi.org/10.1111/j.1538-4632.1981.tb00726.x

Cascetta, E., Cartenì, A., & Montanino, M. (2013). A new measure of accessibility based on perceived opportunities. Procedia-Social and Behavioral Sciences, 87, 117–132.

Cerdá, A. (2009). Accessibility: A performance measure for land-use and transportation planning in the Montréal metropolitan region, supervised research project report. Montreal, Quebec: McGill University School of Urban Planning.

Chegounian, A. (2016). Land-use impact on sustainable transportation. Ishahan, Iran: Isfahan University of Technology.

Chen, B. Y., Yuan, H., Li, Q., Wang, D., Shaw, S.-L., Chen, H.-P., & Lam, W. H. (2016). Measuring place-based accessibility under travel time uncertainty. International Journal of Geographical Information Science, 31(4),783–804.

Chen, X., & Kwan, M.-P. (2012). Choice set formation with multiple flexible activities under space-time constraints. International Journal of Geographical Information Science, 26(5), 941–961.

Church, R. L., & Marston, J. R. (2003). Measuring accessibility for people with a disability. Geographical Analysis, 35(1), 83–96.

Delafontaine, M., Neutens, T., Schwanen, T., & Van de Weghe, N. (2011). The impact of opening hours on the equity of individual space-time accessibility. Computers, Environment and Urban Systems, 35(4), 276–288.

Delafontaine, M., Neutens, T., & Van de Weghe, N. (2012). A GIS toolkit for measuring and mapping space-time accessibility from a place-based perspective. International Journal of Geographical Information Science, 26(6), 1131–1154.

Downs, J. A. (2010). Time-geographic density estimation for moving point objects. Paper presented at the Sixth International Conference on Geographic Information Science, Zurich, September 14–17.

Downs, J. A., & Horner, M. W. (2012). Probabilistic potential path trees for visualizing and analyzing vehicle tracking data. Journal of Transport Geography, 23, 72–80.

El-Geneidy, A. M., & Levinson, D. M. (2006). Access to destinations: Development of accessibility measures.

Envall, P. (2007). Accessibility planning: A chimera? Leeds, England: University of Leeds.

Ettema, D., & Timmermans, H. (2007). Space-time accessibility under conditions of uncertain travel times: Theory and numerical simulations. Geographical Analysis, 39(2), 217–240.

Farber, S., Neutens, T., Miller, H. J., & Li, X. (2013). The social interaction potential of metropolitan regions: A time-geographic measurement approach using joint accessibility. Annals of the Association of American Geographers, 103(3), 483–504.

Ferreira, A., Beukers, E., & Te Brömmelstroet, M. (2012). Accessibility is gold, mobility is not: A proposal for the improvement of Dutch transport-related cost-benefit analysis. Environment and Planning B: Planning and Design, 39(4), 683–697.

Geurs, K. T., & Ritsema van Eck, J. (2001). Accessibility measures: Review and applications. Evaluation of accessibility impacts of land-use transportation scenarios, and related social and economic impact. Bilthoven, The Netherlands: National Institute for Public Health and the Environment, Ministry of Health, Welfare and Sport.

Geurs, K. T., & Van Wee, B. (2004). Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12(2), 127–140.

Hägerstraand, T. (1970). What about people in regional science? Papers in Regional Science, 24(1), 7–24.

Handy, S. L. (2002). Accessibility-vs. mobility-enhancing strategies for addressing automobile dependence in the US. Berekely, CA: University of California Institute of Transportation Studies.

Hansen, W. G. (1959). How accessibility shapes land use. Journal of the American Institute of Planners, 25(2), 73–76.

Hanson, S., & Schwab, M. (1987). Accessibility and intraurban travel. Environment and Planning A, 19(6), 735–748.

He, K., Hu, F., Colditz, G., Manson, J., Willett, W., & Liu, S. (2004). Changes in intake of fruits and vegetables in relation to risk of obesity and weight gain among middle-aged women. International Journal of Obesity, 28(12), 1569–1574.

Horner, M. W., & Downs, J. (2014). Integrating people and place: A density-based measure for assessing accessibility to opportunities. Journal of Transport and Land Use, 7(2), 23–40.

Hung, H.-C., Joshipura, K. J., Jiang, R., Hu, F. B., Hunter, D., Smith-Warner, S. A., ... & Willett, W. C. (2004). Fruit and vegetable intake and risk of major chronic disease. Journal of the National Cancer Institute, 96(21), 1577–1584.

Ingram, D. R. (1971). The concept of accessibility: A search for an operational form. Regional Studies, 5(2), 101–107.

Kim, H.-M., & Kwan, M.-P. (2003). Space-time accessibility measures: A geocomputational algorithm with a focus on the feasible opportunity set and possible activity duration. Journal of Geographical Systems, 5(1), 71–91.

Knox, P. L. (1978). The intraurban ecology of primary medical care: Patterns of accessibility and their policy implications. Environment and Planning A, 10(4), 415–435.

Kwan, M.-P., Murray, A. T., O'Kelly, M. E., & Tiefelsdorf, M. (2003). Recent advances in accessibility research: Representation, methodology and applications. Journal of Geographical Systems, 5(1), 129–138.

Kwan, M.-P., & Weber, J. (2008). Scale and accessibility: Implications for the analysis of land use–travel interaction. Applied Geography, 28(2), 110–123.

Kwan, M. P. (1998). Space‐time and integral measures of individual accessibility: A comparative analysis using a point‐based framework. Geographical Analysis, 30(3), 191–216.

Laube, P., Imfeld, S., & Weibel, R. (2005). Discovering relative motion patterns in groups of moving point objects. International Journal of Geographical Information Science, 19(6), 639–668.

Leal, C., & Chaix, B. (2011). The influence of geographic life environments on cardiometabolic risk factors: A systematic review, a methodological assessment and a research agenda. Obesity Reviews, 12(3), 217–230.

Lenntorp, B. (1977). Paths in space-time environments: A time-geographic study of movement possibilities of individuals. Environment and Planning A, 9(8), 961–972.

Li, Q., Zhang, T., Wang, H., & Zeng, Z. (2011). Dynamic accessibility mapping using floating car data: A network-constrained density estimation approach. Journal of Transport Geography, 19(3), 379–393.

Makri, M.-C., & Folkesson, C. (1999). Accessibility measures for analyses of land use and travelling with geographical information systems. Lund, Sweden: Department of Technology and Society, Lund Institute of Technology.

Malekzadeh, A. (2015). Measurement of transit network accessibility based on access stop choice behavior. Brisbane, Australia: Queensland University of Technology.

Miller, H. (2007). Place‐based versus people‐based geographic information science. Geography Compass, 1(3), 503–535.

Miller, H. J. (1991). Modelling accessibility using space-time prism concepts within geographical information systems. International Journal of Geographical Information System, 5(3), 287–301.

Miller, H. J. (1999). Measuring space‐time accessibility benefits within transportation networks: Basic theory and computational procedures. Geographical Analysis, 31(1), 1–26.

Miller, H. J., & Bridwell, S. A. (2009). A field-based theory for time geography. Annals of the Association of American Geographers, 99(1), 49–75.

Miller, H. J., & Wu, Y.-H. (2000). GIS software for measuring space-time accessibility in transportation planning and analysis. GeoInformatica, 4(2), 141–159.

Nastaran, M., Ghalehnoee, M., & Sahebgharani, A. (2014). Ranking Sustainability of Urban Districts through Factor and Cluster Analyses, Case Study: Municipal Districts of Isfahan ARMANSHAHR Architecture & Urban Development, 12(2), 177-189.

Neutens, T., Delafontaine, M., Scott, D. M., & De Maeyer, P. (2012). An analysis of day-to-day variations in individual space–time accessibility. Journal of Transport Geography, 23, 81–91.

Neutens, T., Schwanen, T., & Witlox, F. (2011). The prism of everyday life: Towards a new research agenda for time geography. Transport Reviews, 31(1), 25–47.

Neutens, T., Schwanen, T., Witlox, F., & De Maeyer, P. (2010). Equity of urban service delivery: A comparison of different accessibility measures. Environment and Planning A, 42(7), 1613–1635.

O'Sullivan, D., Morrison, A., & Shearer, J. (2000). Using desktop GIS for the investigation of accessibility by public transport: An isochrone approach. International Journal of Geographical Information Science, 14(1), 85–104.

Shen, Q. (1998). Location characteristics of inner-city neighborhoods and employment accessibility of low-wage workers. Environment and Planning B: Planning and Design, 25(3), 345–365.

Song, Y. (2015). Green accessibility: Estimating the environmental costs of space-time prisms for Sustainable Transportation Planning. Columbus, Ohio: The Ohio State University.

Song, Y., & Miller, H. J. (2014). Simulating visit probability distributions within planar space-time prisms. International Journal of Geographical Information Science, 28(1), 104–125.

Song, Y., Miller, H. J., Zhou, X., & Proffitt, D. (2016). Modeling visit probabilities within network‐time prisms using Markov techniques. Geographical Analysis, 48(1), 18–42.

Tenkanen, H. (2017). Capturing time in space: Dynamic analysis of accessibility and mobility to support spatial planning with open data and tools. Helsinki: University of Helsinki.

Widener, M. J., Farber, S., Neutens, T., & Horner, M. (2015). Spatiotemporal accessibility to supermarkets using public transit: An interaction potential approach in Cincinnati, Ohio. Journal of Transport Geography, 42, 72–83.

Winter, S., & Raubal, M. (2006). Time geography for ad-hoc shared-ride trip planning. Paper presented at the Mobile Data Management, 7th International Conference. doi: 10.1109/MDM.2006.150

Winter, S., & Yin, Z.-C. (2010). Directed movements in probabilistic time geography. International Journal of Geographical Information Science, 24(9), 1349–1365.

Winter, S., & Yin, Z.-C. (2011). The elements of probabilistic time geography. GeoInformatica, 15(3), 417–434.

Xie, Z., & Yan, J. (2008). Kernel density estimation of traffic accidents in a network space. Computers, Environment and Urban Systems, 32(5), 396–406.

Yu, H., & Shaw, S. L. (2008). Exploring potential human activities in physical and virtual spaces: A spatio‐temporal GIS approach. International Journal of Geographical Information Science, 22(4), 409–430.

DOI: http://dx.doi.org/10.5198/jtlu.2019.1408

Copyright (c) 2019 Alireza Sahebgharani, Hossein Haghshenas & Mahmoud Mohammadi

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