The resource allocation of charging stations is an important part of promoting the development of renewable energy in modern cities. It can promote the scientific and modern construction of urban resource allocation and promote the intelligent transformation of cities. In view of the existing problems in the resource allocation process of urban charging stations, such as a single planning method, considering the actual travel demand. Based on the smart city transportation network information, this article will consider the impact of charging station construction costs, user driving and waiting costs on the location of charging stations, construct a charging station configuration optimization model, and introduce charging convenience coefficients to modify the model. Secondly, this paper establishes a systematic clustering model based on principal component analysis, selecting factors such as per capita GDP, population, and civilian car ownership as indicators, clustering analysis of different regions and assigning different charging convenience coefficients. Finally, the shortest distance matrix between any two nodes is calculated by the Voronoi diagram to concentrate the regional charging load to the traffic node, and the Floyd algorithm is used to analyze and evaluate the effect of the established charging station configuration optimization model. This technology provides a basis for promoting the modernization of urban green transportation.

Public art (PA) is a powerful tool for enhancing the environment in public spaces since it not only relieves the oppression caused by urban architecture but also enhances and beautifies urban public spaces. As DT (digital technology) develops so quickly nowadays, it offers PA significant technological assistance to achieve new functions, and changes in modern people’s aesthetic preferences and psychological makeup also present new demands for PA. This essay explores the use of PA design in the creation of urban landscapes from the viewpoint of DT. In order to do this, this paper suggests a method for measuring the environmental impact of urban landscapes that combines landscape measurement and semantic assessment. Full-connection algorithm and greedy algorithm are introduced to identify urban functional types with high-dimensional characteristics for the boundary tree classification model of high-dimensional feature classification. The findings indicate that the public service area’s producer and user accuracy are, respectively, 0.8783 and 0.7833. It offers a fresh concept for the identification of urban functional zones while solving the issues of low identification efficiency and poor accuracy.