Methodology for Assessing the Transport Accessibility of Capital Objects in a Megacity Based on Geoinformation Data
https://doi.org/10.18184/2079-4665.2021.12.4.400-415
Abstract
Purpose: to present the author's methodology and the test results for calculating integral indicators of transport accessibility on the basis of weighted normalized private indicators for three housing estates in Moscow.
Methods: the study is based on the application of methods for collecting factual material, its processing, systematic, comparative historical and structural-functional analysis, which were supplemented by multivariate analysis of secondary information using content analysis of existing methods for calculating indicators of transport accessibility of capital objects. The results and conclusions of the research are based on the use of the author's methodology for calculating integral indicators of transport accessibility based on weighted normalized private indicators for three housing estates in Moscow. The analysis of a possible set of criteria for assessing transport accessibility of housing estates in Moscow metropolis was carried out on the basis of the use of a geographic information system database GIS NextGIS QGIS.
Results: a review of methodological approaches to the calculation of objective quantitative indicators characterizing the transport accessibility of capital objects is carried out; the author's methodology for calculating the integral indicators of the transport accessibility of residential complexes in Moscow is presented and tested on the basis of weighted normalized private criteria / indicators. The use of the authors’ methodology for calculating integral indicators of transport accessibility based on weighted normalized private criteria / indicators made it possible to calculate the values of indicators of transport accessibility for three housing estates in Moscow, calculate an integrated score for a set of transport accessibility criteria for each housing estate, to give a comparative quantitative assessment of their transport accessibility, to conduct a rating of housing estates in terms of their transport accessibility.
Conclusions and Relevance: the presented results of approbation of the author's methodology for calculating the integral indicators of transport accessibility for housing estates in Moscow allow to conduct a comparative and dynamic analysis of housing estates (or larger units) transport accessibility. The results of such an analysis can be applied in order to develop programs for transport infrastructure development of the megacity as a whole, its certain districts and city parts, as well as to assess such programs efciency. The authors see the directions for future research in the defnition and calculation of indicators based on the city dwellers perception of the transport accessibility
Keywords
About the Authors
S. V. MkhitaryanRussian Federation
Sergey V. Mkhitaryan, Professor of the Marketing Department, Head of the Research Laboratory for Marketing Research of the Transport Complex, Doctor of Economics Sciences
36, Stremyanny lane, Moscow, 117997)
Zh. B. Musatova
Russian Federation
Zhanna B. Musatova, Associate Professor of the Marketing Department, Candidate of Economic Sciences
36, Stremyanny lane, Moscow, 117997
T. V. Murtuzalieva
Russian Federation
Taira V. Murtuzalieva, Associate Professor of the Marketing Department, Candidate of Economic Sciences, Senior Researcher
36, Stremyanny lane, Moscow, 117997
G. S. Timokhina
Russian Federation
Galina S. Timokhina, Associate Professor of the Marketing Department, Candidate of Economic Sciences, Senior Researcher
36, Stremyanny lane, Moscow, 117997
I. P. Shirochenskaya
Russian Federation
Irina P. Shirochenskaya, Associate Professor of the Marketing Department, Candidate of Economic Sciences, Senior Researcher
36, Stremyanny lane, Moscow, 117997
References
1. Curtis C., Scheurer J., McLeod S. Spatial accessibility of public transport in Australian cities: Does it relieve or entrench social and economic inequality? Journal of Transport and Land Use. 2017; 10(1):911-930. https://doi.org/10.5198/jtlu.2017.1097 (In Eng.)
2. Curl A., Nelson J.D., Anable J. Does accessibility planning address what matters? A review of current practice and practitioner perspectives. Research in Transportation Business & Management. 2011; (2):3-11. https://doi.org/10.1016/j.rtbm.2011.07.001(In Eng.)
3. Lättman К., Olsson L.E., Friman M. A new approach to accessibility – Examining perceived accessibility in contrast to objectively measured accessibility in daily travel. Research in Transportation Economics. 2018; (69):501-511. https://doi.org/10.1016/j.retrec.2018.06.002 (In Eng.)
4. Kamruzzaman Md., Yigitcanlar T., Yang J., Mohamed M.A. Measures of Transport-Related Social Exclusion: A Critical Review of the Literature. Sustainability. 2016; 8(7). https://doi.org/10.3390/su8070696 (In Eng.)
5. Tiznado-Aitken I., Munoz J.C., Hurtubia R. Public transport accessibility accounting for level of service and competition for urban opportunities: An equity analysis for education in Santiago de Chile. Journal of Transport Geography. 2021; 90. https://doi.org/10.1016/j.jtrangeo.2020.102919 (In Eng.)
6. Zheng L., van Wee B., Oeser M. Combining accessibilities for different activity types: Methodology and case studyю. Journal of Transport and Land Use. 2019; 12(1):853-872. DOI: 10.5198/jtlu.2019.1529 (In Eng.)
7. De Alba-Martinez H., Grindla AL., OchoaCovarrubias G. (In)Equitable Accessibility to Sustainable Transport from Universities in the Guadalajara Metropolitan Area, Mexico. Sustainability. 2021; 13(1):55. https://doi.org/10.3390/su13010055 (In Eng.)
8. Rossetti S., Tiboni M., Vetturi D., Zazzi M., Caselli B. Measuring Pedestrian Accessibility to Public Transport in Urban Areas: a GIS-based Discretisation Approach. Еuropean transporttrasporti europei. 2020; 76(1). URL: http://www.istiee.unict.it/sites/default/files/files/1_2_ET_14.pdf (accessed 17 October 2021) (In Eng.)
9. Luptak V., Drozdziel P., Stopka O., Stopkova M., Rybicka I. Approach Methodology for Comprehensive Assessing the Public Passenger Transport Timetable Performances at a Regional Scale. Sustainability. 2019; 11(13). https://doi.org/10.3390/su11133532 (In Eng.)
10. Adesanya A. Decision-making for sustainable transport and mobility: Multi actor multi criteria analysis. Social science journal. 2020; 58(2):268-269. https://doi.org/10.1080/03623319.2020.1795520 (In Eng.)
11. Wolek M., Jagiello A., Wolanski M. Multi-Criteria Analysis in the Decision-Making Process on the Electrification of Public Transport in Cities in Poland: A Case Study Analysis. Energies. 2021; 14(19). https://doi.org/10.3390/en14196391(In Eng.)
12. Mikusova N., Fedorko G., Molnar V., Hlatka M., Kampf R., Sirkova V. Possibility of a Solution of the Sustainability of Transport and Mobility with the Application of Discrete Computer Simulation-A Case Study. Sustainability. 2021; 13(17). https://doi.org/10.3390/su13179816 (In Eng.)
13. Siegel M.S. Quantifying transit access in New York City: Formulating an accessibility index for analyzing spatial and social patterns of public transportation. CUNY Academic Workshttp. 2016. https://doi.org/10.1016/j (In Eng.)
14. Casas I., Horner M.W., Weber J. A comparison of three methods for identifying transport-based exclusion: A case study of children’s access to urban opportunities in Erie and Niagara counties, New York. International Journal of Sustainable Transportation. 2009; 3(4):245. https://doi.org/10.1080/15568310802158761 (In Eng.)
15. Broniewicz E., Ogrodnik K. A Comparative Evaluation of Multi-Criteria Analysis Methods for Sustainable Transport. Energies. 2021; 14(6). https://doi.org/10.3390/en14165100 (In Eng.)
16. Yannis V., Kopsacheili A., Dragomanovits A., Petraki V. State-of-the-art review on multi-criteria decision-making in the transport sector. Journal of traffic and transportation engineering. 2020; 7(14):413-431. https://doi.org/10.1016/j.jtte.2020.05.005 (In Eng.)
17. Yampolskaya D.O., Pilipenko A.I. Marketing analysis: technology and methods of implementation. Moscow: Publishing House “Yurayt”; 2018. 268 p. URL: https://urait.ru/bcode/454472 (accessed 11 November 2021) (In Russ.)
18. Podinovsky V.V., Gavrilov V.M. Optimization by consistently applied criteria. Moscow, URSS: LENAND; 2016. 191 p. (In Russ.)
19. Gaft M.G. Decision-making under numerous criteria Moscow, Publishing House “Znanie”; 1979. 64 p. (In Russ.)
20. Belton V., Stewart T.J. Multiple criteria decision analysis. An integrated approach. Boston, Cluwer, 2003. 372 p. (In Eng.)
21. Germeier Yu.V. An introduction to the theory of operations research. Moscow, Publishing House “Nauka”; 1971. 384 p. (In Russ.)
22. Zak Yu.A. Making multi-criteria decisions. Moscow, Publishing House “Economics”; 2011. 235 p. (In Russ.)
23. Tomasiell D.B., Giannotti M., Arbex R., Davis C. Multi-temporal transport network models for accessibility studies. Transactions in GIS.2019; 23(2):203-223. https://doi.org/10.1111/tgis.12513 (In Eng.)
24. Istillozlu E., Doratli N. A normative approach for assessment of accessibility from liveability perspective. European planning studies. 2021; 29(1):39-56. https://doi.org/10.1080/09654313.2020.1779666 (In Eng.)
25. Ľupták V., Bartuška L., Droździel P. Assessing connection quality in passenger air transport in the context of Prague region development. Scientific Journal of Silesian University of Technology. Series Transport. 2019; (103):81-91. https://doi.org/10.20858/sjsutst (In Eng.)
26. Blair N., Hine J., Bukhar S.M.A. Analysing the impact of network change on transport disadvantage: A GIS-based case study of Belfast. Journal of Transport Geography. 2013; (31):192-200. https://doi.org/10.1016/j.jtrangeo.2013.06.015 (In Eng.)
27. Parkhurst G., Meek S. The effectiveness of parkand-ride as a policy measure for more sustainable mobility. Transport and Sustainability. 2014; (5):185-211. (In Eng.)
Review
For citations:
Mkhitaryan S.V., Musatova Zh.B., Murtuzalieva T.V., Timokhina G.S., Shirochenskaya I.P. Methodology for Assessing the Transport Accessibility of Capital Objects in a Megacity Based on Geoinformation Data. MIR (Modernization. Innovation. Research). 2021;12(4):400-415. (In Russ.) https://doi.org/10.18184/2079-4665.2021.12.4.400-415