Classification of Urban Functional Zones Based on Multiple Data Sources

College of Surveying and Geo-Informatics, Tongji University, Shanghai, 200092, China

^* Corresponding author: 2154175@tongji.edu.cn

Abstract

With the rapid development of cities, more and more people are flocking to them. Therefore, cities require good planning to meet the needs of all urban residents. The first step in planning a city is to classify the functional areas of the city. This article introduces a method for classifying urban functional areas in the context of rapid urban population growth, aiming to plan cities better and meet population needs. Based on remote sensing, social perception, and multi-source data, corresponding classification methods were explored, and their roles in urban functional area classification were analyzed. Research has found that focusing remote sensing images on local areas, utilizing social perception data uploaded by passersby, and complimentary use of multi-source data can all improve classification accuracy. The exploration of these methods helps to classify urban functional areas more accurately, providing a better basis for future urban development planning and alleviating the pressure brought by urban population growth.