Detecting Urban Polycentric Structure from POI Data

Abstract

It is meaningful to analyze urban spatial structure by identifying urban subcenters, and many methods of doing so have been proposed in the published literature. Although these methods are widely applied, they exhibit obvious shortcomings that limit their further application. Therefore, it is of great value to propose a new urban subcenter identification method that can overcome these shortcomings. In this paper, we propose the density contour tree (DCT) method for detecting urban polycentric structures and their spatial distributions. Conceptually, this method is based on an analogy between urban spatial structure and terrain. The point-of-interest (POI) density is visualized as a continuous mathematical surface representing the urban terrain. Peaks represent the regions of the most frequent human activity, valleys represent regions with small population densities in the city, and slopes represent spatial changes in urban land-use intensity. Using this method, we have detected the urban “polycentric” structure of Beijing and determined the corresponding spatial relationships. In addition, several important properties of the urban centers have been identified. For example, Beijing has a typical urban polycentric structure with an urban center area accounting for 5.9% of the total urban area, and most of the urban centers in Beijing serve comprehensive functions. In general, the method and the results can serve as references for the later research on analyzing urban structure.

Urban Nighttime Leisure Space Mapping with Nighttime Light Images and POI Data

“…To prevent the generated contour lines from being jagged and irregular, a majority filter in ArcGIS was employed to smooth the composite data to attenuate noise within the data. Since the detected NTL intensity and the POI density of an urban leisure space must be higher than a certain threshold value, we first selected a threshold value as the base contour value, which was determined by using the density-curve method [67]. The core idea is that UNLSs are located in areas with high NTL intensities and POI densities.…”

“…The localized contour tree method is a useful geographic tool that has been used to identify hierarchical relationships from topographic data [68]. In recent years, through improvement and promotion by scholars, this approach also has been successfully used for many purposes, such as map generalization [69], terrain analysis [68], and urban structure analysis [67,70]. In the current work, we use a contour tree to represent the topological relationship between adjacent nodes.…”

Crowdsourced Data Mining for Urban Activity: Review of Data Sources, Applications, and Methods

“…As location-based data, POIs have a strong connection with the urban-built environment. They have been commonly used to explore the physical features of urban areas such as urban form/structure (Pan et al 2018;Song et al 2018;Deng et al 2019), urban boundary, and urban growth (Long et al 2015;Daggitt et al 2016). Based on the subdivided categories of places, a group of researchers use POIs to identify the land use at the store level and detect urban function (Yuan et al 2012;Zhan et al 2014;Frias-Martinez and Frias-Martinez 2014;Liu et al 2017).…”

GIScience Theory Based Assessment of Spatial Disparity of Geodetic Control Points Location

“…where, k() represents the kernel weighting function; s, the center of moving window; and τ, which is greater than 0, the bandwidth. Deng et al [55] demonstrated that the choice of the bandwidth τ has a critical impact on the results of density analysis. As noticed by Gatrell et al [54], increasing the bandwidth results in smoothening of the spatial variation in intensity, while its reduction results in an increasingly 'spiky' estimate.…”