Research on quantitative analysis method of street space quality evaluation——illustrated by the case of Wuhan City Center

With the continuous development of technical means, information technologies such as big data and AI artificial intelligence have gradually become one of the core technical means of planning and design. Using AI and big data to evaluate street space has also become one of the hot spots in recent years. However, there are few studies on the street space quality of Wuhan based on new technology, especially there is almost no evaluation system that combines planning technology and information technology. This article employs multi-source data that combines new technologies and traditional planning methods to evaluate the quality of street space, provides an analytical idea for street planning and construction, and thus guides the future evaluation of street-related implementation projects and street-related planning. This study uses big data, traditional planning data and current status survey data, combined with artificial intelligence, ArcGIS spatial analysis and spatial syntax and other analytical techniques, to propose a comprehensive index system for evaluating street space quality. This paper consists of index system construction, empirical research and results summary. The index system construction refers to the formula construction of the analysis model. Through project literature learning, investigation and research, several quantitative analysis indicators that are most suitable for evaluating the quality of Wuhan streets are selected to form a complete quality evaluation index formula. Empirical research is to select an area in the city center of Wuhan to conduct a case study on the quality evaluation index formula. Lastly, results summary refers to analysis and explanation of the final results, and summary of the research carried out according to the results along with technical problems and technical barriers in the analysis process. It should be particularly pointed out that in this paper, the research object at the material spatial level of street is defined as the following parts: main functional facilities, including motor vehicle lanes, bus lanes, motor vehicle parking belts, non-motor vehicle lanes and sidewalks, etc.; ancillary functional facilities, including street greening, street furniture, municipal facilities, isolation facilities, pedestrian crossings, and safety facilities, etc.; spatial interfaces, including facade shapes, colors, and ancillary facilities along the street. The data adopted mainly comes from street view image data of Internet map open platform, POI data of Internet open platform, traditional planning and design drawing data and current situation survey data.