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Assessing recreationists’ preferences of the landscape and species using crowdsourced images and machine learning

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Abdesslam Chai-allah
  • Johannes Hermes
  • Anne De La Foye
  • Zander S. Venter

Research Organisations

External Research Organisations

  • Blaise Pascal University
  • Norwegian Institute for Nature Research (NINA)
  • University of Michigan

Details

Original languageEnglish
Article number105315
JournalLandscape and urban planning
Volume257
Early online date9 Feb 2025
Publication statusPublished - May 2025

Abstract

Crowdsourced data are now well-established for assessing cultural ecosystem services (CES). In rural areas, understanding which land covers people prefer to recreate in, and how these land covers provide different CES, is necessary to support sustainable use. In this study, we aim to assess recreationists’ revealed preferences of landscape aesthetics and species observation as two CES, considering multiple land cover types in a rural area in France. This assessment was carried out using georeferenced images from two crowdsourced sources (Flickr and Wikiloc) and by analyzing their content using a machine-learning algorithm. We further developed a framework to classify images based on their content into CES-related images (those depicting landscapes or species) and non-CES-related images. Finally, we assessed how images depicting landscape aesthetics and species observation are distributed across the land covers visited by recreationists, and which species groups are the most photographed. Our results showed the dominance of images of open landscape views over close-up species images, and that grasslands are the primary providers of open views. In addition, we found that forests also provide open landscape views, suggesting that forests with gaps in canopy cover and viewpoints can be as important as grasslands in providing aesthetic views, especially in hilly landscapes. For species, the category “plants and flowers“ was the most photographed, followed by invertebrates and birds on Flickr, and domestic livestock on Wikiloc. This study provides insights into the importance of using multiple crowdsourced sources in CES assessment, providing critical insights for both landscape managers and conservationists.

Keywords

    Cultural ecosystem services, Image content analysis, Landscape aesthetics, Social media, Species observation

ASJC Scopus subject areas

Sustainable Development Goals

Cite this

Assessing recreationists’ preferences of the landscape and species using crowdsourced images and machine learning. / Chai-allah, Abdesslam; Hermes, Johannes; La Foye, Anne De et al.
In: Landscape and urban planning, Vol. 257, 105315, 05.2025.

Research output: Contribution to journalArticleResearchpeer review

Chai-allah, A., Hermes, J., La Foye, A. D., Venter, Z. S., Joly, F., Brunschwig, G., Bimonte, S., & Fox, N. (2025). Assessing recreationists’ preferences of the landscape and species using crowdsourced images and machine learning. Landscape and urban planning, 257, Article 105315. https://doi.org/10.1016/j.landurbplan.2025.105315
Chai-allah A, Hermes J, La Foye AD, Venter ZS, Joly F, Brunschwig G et al. Assessing recreationists’ preferences of the landscape and species using crowdsourced images and machine learning. Landscape and urban planning. 2025 May;257:105315. Epub 2025 Feb 9. doi: 10.1016/j.landurbplan.2025.105315
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