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Landscape Efficiency Assessment of Urban Subway Station Entrance Based on Structural Equation Model: Case Study of Main Urban Area of Nanjing

Public landscape efficiency is one of the research hotspots in contemporary landscape performance. The renewal of micro landscape space has positive effects on community vitality and the sustainable development of landscape resources. The subway station entrance is a typical representative of the miniature landscape environment. To improve the construction of subway station entrances, clear cognition on the landscape efficiency of subway station entrances and their impact indicators is necessary. For this purpose, a structural equation model with a parameter system was established to measure landscape efficiency. There are four latent variables (e.g., traffic capacity) and 10 observed variables (e.g., visual level) composed of an estimation model. Researchers selected 131 subway station entrances in the main urban area of Nanjing as survey samples. Various methods, including investigation, image recognition, and modelling analysis, were comprehensively used to analyse the landscape characteristics of the subway station entrances quantitatively. A calculation was conducted to obtain the correlation coefficient of latent variables and the explanatory degree of observed variables. The result shows that green space landscapes and traffic capacity impresses the landscape efficiency of subway station entrances. Furthermore, all these variables have complex correlations. The fluctuation of any latent variable may cause the decay or enhancement of related variables. Therefore, designers should have a comprehensive cognition of the landscape environment of subway station entrances to enable them to propose balanced design strategies under traffic, visibility, plants and facilities. This paper aims to help designers gain an in-depth understanding of the ideal landscape construction forms at subway station entrances and facilitate the high-quality development of the urban landscape environment.