Evaluation of the Visual Perception of Urban Single/Double-Layer Riverfront Greenway Landscapes Based on Deep Learning DOI Open Access
Xin Li,

Yuan Wang,

Zhenyu Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10391 - 10391

Published: Nov. 27, 2024

Urban inland rivers are closely related to urban development, but high-density urbanisation has reduced the natural function of streams and riverbanks hardened into two parts, embankment walls berms, which give rise a variety riparian landscapes. However, difference in height walkways affects degree their greening landscape effects. In this paper, we studied single- double-decker greenways, constructed quantitative indicators spatial elements based on deep learning algorithms using an image semantic segmentation (ISS) model that simulates human visual perception, used random forests multivariate linear regression models study impact riverfront greenway clarified differences caused by different types space aesthetic preferences (LP) confirmed specific extent components influence preferences. The results showed there were significant perception scores between single double layers. (1) WED (negative correlation) NI (positive is large single-layer greenway. colour, material structure guardrail can be beautified diversified quality greenery taken account maintain visibility order improve score (2) BVI double-layered positive. Water-friendly or water-viewing spaces added appropriately greenways. This applicable regional feature identification greenways large-scale hard barge bank images, realises whole-region perspective effective expansion analysis techniques for sustainable planning design

Language: Английский

Evaluation of the Visual Perception of Urban Single/Double-Layer Riverfront Greenway Landscapes Based on Deep Learning DOI Open Access
Xin Li,

Yuan Wang,

Zhenyu Wang

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(23), P. 10391 - 10391

Published: Nov. 27, 2024

Urban inland rivers are closely related to urban development, but high-density urbanisation has reduced the natural function of streams and riverbanks hardened into two parts, embankment walls berms, which give rise a variety riparian landscapes. However, difference in height walkways affects degree their greening landscape effects. In this paper, we studied single- double-decker greenways, constructed quantitative indicators spatial elements based on deep learning algorithms using an image semantic segmentation (ISS) model that simulates human visual perception, used random forests multivariate linear regression models study impact riverfront greenway clarified differences caused by different types space aesthetic preferences (LP) confirmed specific extent components influence preferences. The results showed there were significant perception scores between single double layers. (1) WED (negative correlation) NI (positive is large single-layer greenway. colour, material structure guardrail can be beautified diversified quality greenery taken account maintain visibility order improve score (2) BVI double-layered positive. Water-friendly or water-viewing spaces added appropriately greenways. This applicable regional feature identification greenways large-scale hard barge bank images, realises whole-region perspective effective expansion analysis techniques for sustainable planning design

Language: Английский

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