Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling

Xueqian Gong, Zhanyuan Zhu (), Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li and Yujie Huang
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Xueqian Gong: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Zhanyuan Zhu: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Li Guo: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Yong Zhong: CECEP (ChengDu) Ecological Environment Protection Industrial Co., Ltd., Chengdu 610400, China
Deshun Zhang: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Jing Li: College of Architecture and Urban-Rural Planning, Sichuan Agricultural University, Chengdu 611830, China
Manqin Yao: College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
Wei Yong: School of Physics, University of Electronic Science and Technology of China, Chengdu 610054, China
Mengjia Li: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China
Yujie Huang: College of Landscape Architecture, Sichuan Agricultural University, Chengdu 611130, China

Land, 2025, vol. 14, issue 5, 1-18

Abstract: Xishu Gardens, an exemplary narrative of classical Chinese gardens, faces challenges in preserving its commemorative spatial structures while accommodating modern visitors’ needs. While trajectory analysis is critical, existing studies struggle to interpret multi-dimensional perception-preference data owing to spatiotemporal mismatches in multi-source datasets. This study adopted an improved Ward–K-medoids hybrid clustering algorithm to analyze 885 trajectory samples and 34,384 synchronized data points capturing emotional valence, cognitive evaluations, and dwell time behaviors via panoramic digital twins across three heritage sites (Du Fu Thatched Cottage, San Su Shrine, and Wangjiang Tower Park). Our key findings include the following: (1) Axial bimodal patterns: Type I high-frequency looping paths (27.6–68.9% recurrence) drive deep exploration, in contrast to Type II linear routes (≤0.5% recurrence), which enable intensive node coverage. (2) Layout-perception dynamics: single-axis layouts maximize behavioral engagement (DFTC), free-form designs achieve optimal emotional-cognitive integration (WTP), and multi-axis systems amplify emotional-cognitive fluctuations (SSS). (3) Spatial preference hierarchy: entrance and waterfront zones demonstrate dwell times 20% longer than site averages. Accordingly, the proposed model synchronizes Type II peak-hour throughput with Type I off-peak experiential depth using dynamic path allocation algorithms. This study underscores the strong spatial guidance mechanisms of Xishu Gardens, supporting tourism management and heritage conservation.

Keywords: perceptual preference; Xishu Gardens; tourist route; panoramic imaging; machine learning (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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