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Mapeo de valores paisajísticos impulsado por IA

David Jovanovikj1,2, Marija Stojcheva2, Viktor Domazetoski1,3,4

  • 1Macedonian Academy of Sciences and Arts, Blvd. Krste Misirkov 2, 1000 Skopje, Republic of Macedonia.

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Resumen
Este resumen es generado por máquina.

La Inteligencia Artificial-Perceptual Landscape Mapping (AI-PLM) utiliza datos de redes sociales para comprender la percepción humana del paisaje. Este marco AI-PLM revela puntos críticos clave de apreciación y conexiones emocionales con sitios naturales y patrimoniales en Rumania.

Palabras clave:
percepción del paisajeinteligencia artificialredes socialesservicios ecosistémicos culturalesteledetecciónanálisis de sentimientosmodelado de temas

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Área de la Ciencia:

  • Ciencias Ambientales
  • Inteligencia Geoespacial
  • Ciencias Sociales Computacionales

Sus antecedentes:

  • Los métodos tradicionales de percepción del paisaje carecen de escala y alcance.
  • Comprender la percepción humana es crucial para la conservación y la planificación.
  • Los datos de redes sociales ofrecen un recurso vasto y sin explotar para estudios de paisajes.

Objetivo del estudio:

  • Introducir y validar el marco AI-Perceptual Landscape Mapping (AI-PLM).
  • Modelar la percepción humana colectiva del paisaje utilizando datos de redes sociales.
  • Evaluar los servicios ecosistémicos culturales a través del análisis impulsado por IA.

Principales métodos:

  • Marco AI-PLM integrado que combina inteligencia geoespacial, aprendizaje automático y PNL.
  • Análisis de fotografías de Flickr georreferenciadas y comentarios de usuarios de Rumania.
  • IA-Cognición Espacial (métodos Head/Tail Breaks, DBSCAN, análisis de vistas) e Inteligencia Afectivo-Semántica (análisis de sentimientos, modelado de temas).

Principales resultados:

  • Se identificaron fuertes jerarquías espaciales de apreciación del paisaje, con picos en los Cárpatos, Brașov, Bucarest, Maramureș y la costa del Mar Negro.
  • El análisis de sentimientos reveló emociones predominantemente positivas vinculadas a regiones orientadas a la naturaleza.
  • El modelado de temas destacó temas de fotografía, patrimonio y recreación en el contenido generado por los usuarios.

Conclusiones:

  • AI-PLM proporciona una metodología escalable y transferible para evaluar los servicios ecosistémicos culturales.
  • El marco une la geografía física y la expresión emocional para el análisis del paisaje.
  • AI-PLM ofrece herramientas prácticas para la gestión del paisaje basada en datos, la conservación y la planificación del turismo.