Research on the Spatial Structure of Xinjiang Port Cities Based on Multi-Source Geographic Big Data—A Case of Central Kashi City

Abstract

Exploring urban spatial structure plays an important role in promoting urban development, but there is a lack of research on the urban spatial structure of Xinjiang ports. This paper takes the central urban area of Kashi City as the study area and integrates points of interest (POI) data with nighttime light (NTL) data using the Open Street Map (OSM) road network to perform kernel density analysis, two-factor combination mapping, and partition identification. It identifies the spatial structural characteristics of the central urban area and divides it into different functional subdivisions. This research shows that ① the overall distributions of nighttime luminance values and POI kernel density are similar, and the overall distribution pattern gradually weakens from the city centre to the surrounding area. High-value areas are distributed in groups, presenting the spatial structure characteristics of one main area and two subareas. ② The fusion of POI data with OSM road network data identifies urban single functional zones and mixed functional zones and divides different functional zones in a more detailed way, with higher accuracy in identifying functional zones. ③ The coupling of POI and nighttime light remote sensing can better characterise the spatial features of the urban structure, such as large-scale homogeneous areas, urban fringe areas, suburbs and township centres, etc. The fusion of POI and the OSM road network can better characterise single and mixed land use types of urban land use and improve the part of the city that cannot be characterised by POI and night light. The results of this study are conducive to the realisation of rational and functional zoning in Kashi City and provide a reference for promoting urban human–land coordination and sustainable development.