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Assessing Recreational Load in Russia: A Multi-Scale Approach Using Big Data

Author

Listed:
  • E. Yu. Kolbovsky

    (Lomonosov Moscow State University
    Institute of Geography, Russian Academy of Sciences)

  • O. A. Klimanova

    (Lomonosov Moscow State University)

Abstract

The article considers the possibilities of using a particular type of big data, geolocalized photographs, as an objective indicator of the spatial distribution and intensity of the tourist and recreation load within the tourist macroregion From Moscow to St. Petersburg, allocated under the State Program of the Russian Federation “Tourism Development.” The study uses an original geoinformation model compiled from freely available OpenStreetMap layers and photographic locations localized in space and time. It allows, on the one hand, to characterize the specific features of the location of attractors (natural, cultural) and tourist and recreational infrastructure, on the other hand, to objectively assess the spatial distribution of the presence of tourists and recreationists within the macroregion and describe the specifics of their intra-annual (seasonal) “attraction.” Aggregation of photographing points into polygons taking into account differentiated clustering distances made it possible to form areas of seasonal (summer, winter and spring-autumn) stay of tourists, as well as to obtain an idea of the minimum year-round and maximum sporadic areas within the macroregion and individual areas exposed to the potential impact of tourists and recreants. It is proposed to use the differences between the minimum and maximum areas of stay of tourists and recreationists to assess the efficiency of the sector in the oblasts of the macroregion. The resulting spatial geographic ranges and patterns of tourist presence open up opportunities for an objective assessment of the potential load on natural and cultural heritage sites. The uneven inclusion of both natural and cultural attractors in the sphere of tourism and recreation has been revealed, which leads to a situation where some objects of natural and cultural heritage experience significant industry pressure, while others remain almost or completely unaffected by the presence of tourists and recreationists. The discovered weaknesses of using geolocalized photographic images to assess the distribution and intensity of recreational load are the impossibility of separating local and transitory flows of tourists and bringing the total volume of photographs to the number of users. However, these circumstances can be overcome with the participation of stakeholders: data holders and managers of the tourist and recreational sector.

Suggested Citation

  • E. Yu. Kolbovsky & O. A. Klimanova, 2024. "Assessing Recreational Load in Russia: A Multi-Scale Approach Using Big Data," Regional Research of Russia, Springer, vol. 14(3), pages 478-492, September.
    • Handle: RePEc:spr:rrorus:v:14:y:2024:i:3:d:10.1134_s2079970524600355
    DOI: 10.1134/S2079970524600355
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    References listed on IDEAS

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    1. V. R. Bityukova, 2022. "Environmental Consequences of the Transformation of the Sectoral Structure of the Economy of Russian Regions and Cities in the Post-Soviet Period," Regional Research of Russia, Springer, vol. 12(1), pages 96-111, March.
    2. E. Yu. Kolbovsky & U. A. Medovikova, 2017. "Assessment of the aesthetic landscape properties for managing areas of outstanding natural beauty and historical significance," Regional Research of Russia, Springer, vol. 7(1), pages 81-88, January.
    3. Yoshimura, Nobuhiko & Hiura, Tsutom, 2017. "Demand and supply of cultural ecosystem services: Use of geotagged photos to map the aesthetic value of landscapes in Hokkaido," Ecosystem Services, Elsevier, vol. 24(C), pages 68-78.
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