A Study on the Cognition of Urban Spatial Image at Community Scale: A Case Study of Jinghu Community in Zhengzhou City

Abstract

The community is the basic spatial unit for urban residents to live and rest. It is a crucial direction of city image research to explore people’s cognitive characteristics of community space image. Aiming at the lack of cognitive quantification of community spatial images, a new method that can quantify community spatial data into cognitive results is proposed. By employing spatial analysis tools, eleven spatial indicators from the perspective of community spatial form and spatial services are selected, and an image structure is constructed based on the characteristics of the indicator results. The results of multiple indicators are organized through the improved technique for order preference by similarity to ideal solution (TOPSIS) and overlay analysis method to produce a spatial image map of the community. The study displays that the spatial image characteristics of the community scale can be comprehensively expressed through three types of elements: district, path (edge), and node (landmark). These three types of elements constitute the image structure at the community scale and present apparent elements’ characteristics. This scrutiny is also aimed to demonstrate the construction and use process of the methodology and to provide new ideas for the cognitive research of urban spatial image at the community scale.

Urban Spatial Image Acquisition and Examination Based on Geographic Big Data

“…The current research scale is mainly divided into two categories. On a microscale, research mainly studies tourist destinations [9], communities [10], campuses [11], and other spaces in the city. The second research scale involves the exploration of one city [6,12], multiple cities [7], and even urban agglomerations at the macroscale [13].…”