Geoinformation-based assessment of urban street network attractiveness for cycling in Russian cities

DOI: 10.35595/2414-9179-2025-3-31-349-362

View or download the article (Rus)

About the Authors

Elena S. Zaslavskaya

Lomonosov Moscow State University, Faculty of Geography,
1, Leninskie Gory, Moscow, 119991, Russia,
E-mail: elenka.zaslavskaya@mail.ru

Andrey M. Karpachevskiy

Lomonosov Moscow State University, Faculty of Geography,
1, Leninskie Gory, Moscow, 119991, Russia,
E-mail: karpach-am@yandex.ru

Abstract

This paper proposes a comprehensive methodology for assessing the attractiveness of urban street networks for cycling based on open spatial data and network analysis tools. The methodology is designed for cities lacking complete statistics on street network characteristics. The input data include OpenStreetMap, very high-resolution remote sensing data, and a street-view imagery service. The proposed composite index integrates 13 factors reflecting the safety and comfort of cycling. Factor weights were calculated using two approaches: (1) objectively, through information entropy, and (2) subjectively, based on a questionnaire survey of five target cyclist groups. The methodology was tested in Almetyevsk, Kostroma, and Kaliningrad—three Russian cities representing different urban typologies. The results make it possible to accurately describe the current state of cycling infrastructure and identify spatial priorities for its improvement. Almetyevsk demonstrates a high connectivity of segments with favorable conditions; Kostroma is characterized by a fragmented cyclist-friendly environment; Kaliningrad combines high- and low-quality segments, indicating the need for targeted modernization. The methodology can be used in municipal planning, transport modeling, and the development of sustainable mobility strategies. The universality of the input data ensures its scalability and applicability to a wide range of Russian and international cities. Moreover, it can support monitoring of cycling conditions over time, identify spatial disparities in infrastructure accessibility, justify investment priorities, and improve decision-making transparency across diverse urban contexts.

Keywords

cycling, attractiveness index, network analysis, OpenStreetMap, urban mobility

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For citation: Zaslavskaya E.S., Karpachevskiy A.M. Geoinformation-based assessment of urban street network attractiveness for cycling in Russian cities. InterCarto. InterGIS. Moscow: MSU, Faculty of Geography, 2025. V. 31. Part 3. P. 349–362. DOI: 10.35595/2414-9179-2025-3-31-349-362 (in Russian)