Construction and Integrated Design of Urban Landscape Space System Based on Deep Learning

Abstract

In the rapid process of urbanization, human production and living activities continuously interact and influence with urban space. With the improvement of the quality of life of urban residents, people will have higher and higher requirements for outdoor activities, so the status of public space in cities will become more and more important. More and more rural people are entering cities, carrying out more efficient economic activities and enjoying modern urban civilization. Entering the new century, China's urbanization will move towards a larger scale and higher quality. In the past, the reconstructed urban public space lacked authenticity, and some scholars used laser scanner to carry out 3D digital reconstruction, which had high modeling accuracy. However, the reconstructed scene did not have texture information, so its authenticity was poor and the cost was extremely high. In this paper, the construction and integration design method of urban public space system based on deep learning is proposed to improve modeling accuracy and scene authenticity.