Effects of River Scale on the Aesthetic Quality of Urban On-Water Sightseeing

Xin Li, Xiangrong Wang, Jingyi Han, Danzi Wu (), Qing Lin (), Jiayi Zhou and Shujie Zhao
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Xin Li: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Xiangrong Wang: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Jingyi Han: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Danzi Wu: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Qing Lin: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Jiayi Zhou: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China
Shujie Zhao: School of Landscape Architecture, Beijing Forestry University, Beijing 100083, China

Sustainability, 2022, vol. 14, issue 19, 1-16

Abstract: On-water sightseeing plays a key role in the tourism of traditional Chinese landscapes. The on-water landscape affects tourism potential and the quality of urban landscapes. Current research on river landscape is mainly based on remote sensing images or on-land approaches, while studies of on-water perspective landscapes at different river scales is lacking. In this paper, with Guilin city rivers taken as an example, we adopt image semantic segmentation technology to evaluate the visual landscape characteristics under different river scales, and subsequently employ automatic linear modeling to screen important factors affecting aesthetic quality. The results reveal the obvious differences between the on-water landscape characteristics of different scale rivers. The on-water landscape quality of large- and small-scale rivers is mainly affected by seven and four factors, respectively. The Karst landform of Guilin is observed to significantly improve the on-water landscape quality of large-scale rivers. By considering the impact mechanism of landscape composition on the aesthetic quality and the different scale rivers, we propose several aesthetic quality improvement strategies based on low-cost methods, including the planting of vegetation and the micro renewal of artificial constructions. This study contributes to the intelligent evaluation of urban on-water landscape and provides reference for on-water route selection and urban planning.

Keywords: visual perception; semantic image segmentation; on-water landscape; river scale; landscape features; Guilin (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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