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A comprehensive framework for automated identification of cultural ecosystem services

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  • Kovárník, Richard
  • Janová, Jitka
  • Hampel, David

Abstract

Cultural ecosystem services (CES) represent intangible values, making them inherently challenging to analyze. In this study, we present a framework that combines web scraping, text mining, and statistical analysis to gain deeper insights into how people perceive valuable ecosystems and the benefits they derive from them. A total of 4,760 public reviews were collected from the Google Maps platform using dynamic web scraping techniques. Machine learning-based topic modelling was then applied to identify key themes related to CES in selected national parks and protected areas across the Czech Republic. Finally, we tested the hypothesis that the relative frequency of specific topics varies significantly between locations. The proposed approach proved effective in the automated evaluation of CES and in highlighting the distinctive features of the studied sites.

Suggested Citation

  • Kovárník, Richard & Janová, Jitka & Hampel, David, 2025. "A comprehensive framework for automated identification of cultural ecosystem services," Ecosystem Services, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:ecoser:v:75:y:2025:i:c:s2212041625000749
    DOI: 10.1016/j.ecoser.2025.101770
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    References listed on IDEAS

    as
    1. Fox, Nathan & Graham, Laura J. & Eigenbrod, Felix & Bullock, James M. & Parks, Katherine E., 2021. "Reddit: A novel data source for cultural ecosystem service studies," Ecosystem Services, Elsevier, vol. 50(C).
    2. Daněk, Jan & Blättler, Linda & Leventon, Julia & Vačkářová, Davina, 2023. "Beyond nature conservation? Perceived benefits and role of the ecosystem services framework in protected landscape areas in the Czech Republic," Ecosystem Services, Elsevier, vol. 59(C).
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    4. Havinga, Ilan & Bogaart, Patrick W. & Hein, Lars & Tuia, Devis, 2020. "Defining and spatially modelling cultural ecosystem services using crowdsourced data," Ecosystem Services, Elsevier, vol. 43(C).
    5. Paulina Guerrero & Maja Steen Møller & Anton Stahl Olafsson & Bernhard Snizek, 2016. "Revealing Cultural Ecosystem Services through Instagram Images: The Potential of Social Media Volunteered Geographic Information for Urban Green Infrastructure Planning and Governance," Urban Planning, Cogitatio Press, vol. 1(2), pages 1-17.
    6. Cardoso, Ana Sofia & Renna, Francesco & Moreno-Llorca, Ricardo & Alcaraz-Segura, Domingo & Tabik, Siham & Ladle, Richard J. & Vaz, Ana Sofia, 2022. "Classifying the content of social media images to support cultural ecosystem service assessments using deep learning models," Ecosystem Services, Elsevier, vol. 54(C).
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