Research on renewal and transformation of urban negative space based on AI spatial identification technology

Abstract

This paper aims to study the renewal and transformation of urban negative space based on AI spatial identification technology, and takes Deya Road in Changsha as a typical case for field investigation. On the basis of data analysis based on the establishment of the standard model, through the feature analysis of Deya Road negative space and the data analysis of the standard model, combined with AI image space recognition technology and algorithm-based logical thinking, the paper summarizes the spatial feature points of the negative space for digital translation, providing data sources and evaluation criteria for AI machine learning. At the same time, the probability of success of spatial identification and spatial model library are established. Combining with the record of quantitative data, the positive countermeasures are put forward for the negative spatial remodeling of streets.