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Summary
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Artificial intelligence-Perceptual Landscape Mapping (AI-PLM) uses social media data to understand human landscape perception. This AI-PLM framework reveals key appreciation hotspots and emotional connections to natural and heritage sites in Romania.

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Area of Science:

  • Environmental Science
  • Geospatial Intelligence
  • Computational Social Science

Background:

  • Traditional landscape perception methods lack scale and scope.
  • Understanding human perception is crucial for conservation and planning.
  • Social media data offers a vast, untapped resource for landscape studies.

Purpose of the Study:

  • To introduce and validate the AI-Perceptual Landscape Mapping (AI-PLM) framework.
  • To model collective human perception of landscapes using social media data.
  • To assess cultural ecosystem services through AI-driven analysis.

Main Methods:

  • Integrated AI-PLM framework combining geospatial intelligence, machine learning, and NLP.
  • Analysis of geotagged Flickr photographs and user comments from Romania.
  • AI-Spatial Cognition (Head/Tail Breaks, DBSCAN, viewshed analysis) and Affective-Semantic Intelligence (sentiment, topic modeling).

Main Results:

  • Identified strong spatial hierarchies of landscape appreciation, with peaks in the Carpathians, Braşov, Bucharest, Maramureş, and the Black Sea coast.
  • Sentiment analysis revealed predominantly positive emotions linked to nature-oriented regions.
  • Topic modeling highlighted themes of photography, heritage, and recreation in user-generated content.

Conclusions:

  • AI-PLM provides a scalable and transferable methodology for assessing cultural ecosystem services.
  • The framework bridges physical geography and emotional expression for landscape analysis.
  • AI-PLM offers practical tools for data-driven landscape management, conservation, and tourism planning.