A Study on the Regional Evolution of the Hefei Political and Cultural New District Skyline Based on Exploratory Factor Analysis and Semantic Segmentation

Abstract

The general population’s assessment and perception of a city can be influenced by its skyline, which is one of its representatives. This paper uses semantic segmentation and exploratory factor analysis to conduct a study from two different perspectives, aiming to analyse the development and current situation of the skyline of Hefei’s political and cultural new district. By collecting pictures of the skyline of the New Administrative and Cultural District, the New Administrative and Cultural District of Hefei’s skyline is being studied for overall changes using the semantic segmentation method, and to evaluate the quality of the skyline in various years, the entropy weight–TOPSIS is employed. Through the literature investigation and creation status of the new political and cultural district, the index system is scientifically formulated to conduct a questionnaire survey, and its reliability and validity are tested. This study is conducted with exploratory factor analysis of factors that are vital in the city skyline. The results of this study show that (1) after the semantic segmentation of the pictures, it is found that the proportion of buildings and the proportion of vegetation are both rising; the proportion of buildings tends to level off after 2018, and the proportion of vegetation shows a uniform increase. In the relative proximity ranking, the overall trend is increasing, and the skyline is ranked first in 2024. (2) Two variables were identified based on the findings of the exploratory factor analysis: ‘skyline value’ and ‘neighbourhood ecological quality’. The results of this study show that the skyline of Hefei’s New Administrative and Cultural District in 2024 is the best overall, and that the skyline of the New Administrative and Cultural District has developed into one of the city images of Hefei, and that its optimisation can be considered in terms of the “quality of the surrounding ecological environment”.

Keywords

• city skyline
• urban image
• semantic segmentation approach
• exploratory factor analysis