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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
