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Visual Quality Assessment of Rural Landscapes Based on Eye-Tracking Analysis and Subjective Perception

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  • Yu Li

    (Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China
    College of Horticulture and Landscape Architecture, Northeast Agricultural University, Harbin 150030, China
    These authors contributed equally to this work.)

  • Hao Luo

    (Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China
    These authors contributed equally to this work.)

  • Siqi Sun

    (Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China
    College of Horticulture and Landscape Architecture, Northeast Agricultural University, Harbin 150030, China)

  • Kun Wang

    (College of Horticulture and Landscape Architecture, Northeast Agricultural University, Harbin 150030, China)

  • Qing Zhao

    (Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization, Guangdong Academy of Forestry, Guangzhou 510520, China)

Abstract

Traditional visual quality assessments of rural landscapes rely on subjective methods. This study integrates eye-tracking technology with subjective perception evaluation to construct a visual quality assessment model for rural landscapes, aiming to reveal the intrinsic relationship between objective visual behavior and subjective perception, with the aim of providing scientific guidance for rural landscape planning to promote sustainable rural development. Using landscape photographs from nine rural sampling sites in Guangzhou, eye-tracking experiments were conducted to collect participants’ eye movement data, combined with online questionnaires to obtain scenic beauty ratings and landscape characteristic factor evaluations. The findings reveal the following: (1) Eye-tracking experiments and subjective evaluation results showed high consistency, with samples having higher scenic beauty ratings demonstrating more prominent performance in core eye movement indicators such as total fixation duration and count, and total saccade duration, and typically possessing higher landscape characteristic factor values. (2) Urban–suburban-integrated rural landscapes exhibited poorer visual quality, characteristic-preservation rural landscapes elicited more in-depth and sustained visual exploration, and clustered-improvement rural landscapes possessed higher scenic beauty ratings and landscape characteristic factor values. (3) Total saccade duration was the key eye movement indicator for predicting scenic beauty ratings. (4) Multiple landscape characteristic factors significantly influence eye movement behavior.

Suggested Citation

  • Yu Li & Hao Luo & Siqi Sun & Kun Wang & Qing Zhao, 2025. "Visual Quality Assessment of Rural Landscapes Based on Eye-Tracking Analysis and Subjective Perception," Sustainability, MDPI, vol. 18(1), pages 1-28, December.
  • Handle: RePEc:gam:jsusta:v:18:y:2025:i:1:p:161-:d:1824666
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