Measuring the Spatial Allocation Rationality of Service Facilities of Residential Areas Based on Internet Map and Location-Based Service Data

Abstract

The spatial allocation rationality of the service facilities of residential areas, which is affected by the scope of the population and the capacity of service facilities, is meaningful for harmonious urban development. The growth of the internet, especially Internet map and location-based service (LBS) data, provides micro-scale knowledge about residential areas. The purpose is to characterize the spatial allocation rationality of the service facilities of residential areas from Internet map and LBS data. An Internet map provides exact geographical data (e.g., points of interests (POI)) and stronger route planning analysis capability through an application programming interface (API) (e.g., route planning API). Meanwhile, LBS data collected from mobile equipment afford detailed population distribution values. Firstly, we defined the category system of service facilities and calculated the available service facilities capacity of residential areas (ASFC-RA) through a scrappy algorithm integrated with the modified cumulative opportunity measure model. Secondly, we used Thiessen polygon spatial subdivision to gain the population distribution capacity of residential areas (PDC-RA) from Tencent LBS data at the representative moment. Thirdly, we measured the spatial allocation rationality of service facilities of residential areas (SARSF-RA) by combining ASFC-RA and PDC-RA. In this case, a trial strip census, consisting of serval urban residential areas from Wuxi City, Jiangsu Province, is selected as research area. Residential areas have been grouped within several ranges according to their SARSF-RA values. Different residential areas belong to different groups, even if they are spatially contiguous. Spatial locations and other investigation information coordinate with these differences. Those results show that the method that we proposed can express the micro-spatial allocation rationality of different residential areas dramatically, which provide a new data lens for various researchers and applications, such as urban residential areas planning and service facilities allocation.

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

“…Thiessen polygons, also called Voronoi diagrams, define individual areas of influence around each of a set of points, hence any location within a Thiessen polygon is closer to its linked point than to any other [60]. This property has caused that Thiessen polygons are perceived as a proper construct to test the CSR hypothesis as well as the regularity of spatial distribution [61,62]. In considering the equal division characteristics of the Thiessen polygon in spatial tessellation, the method can be used to investigate such issues as nearest points, proximity, adjacency, and accessibility analyses [63].…”

Measuring spatiotemporal accessibility for pediatric clinical services with multimodal transport modes: an exploratory analysis in Nanjing, China

“…Traditional studies look towards subjectively choosing specific travel modes (F. Wang, 2012), but an increasing number of scholars have begun to improve accessibility models considering the influence of different transport modes (Dony, Delmelle, & Delmelle, 2015). Travel impedance data can be accessed from open data sources (García-Albertos, Picornell, Salas-Olmedo, & Gutiérrez, 2018;Weiss et al, 2018), including individual trip survey data (Mao & Nekorchuk, 2013), web mapping service (Google Maps (Dony et al, 2015), Baidu Maps (Tao, Yao, Kong, Duan, & Li, 2018), Amap Maps (Zhou, Ding, Wu, Huang, & Hu, 2019)) and location-based social media data (T. Zhang et al, 2018), which enable advancements in revealing the characteristics of human activities (Huang, Levinson, Wang, Zhou, & Wang, 2018;Y. Liu et al, 2015;Xu et al, 2016).…”

“…Population spatial distribution data are one of the essential indicators for realizing spatiotemporal accessibility (Zhou et al, 2019). Similarly, the spatial distribution data for children are the key to evaluating STA-PCS.…”

Emerging Location-Based Service Data on Perceiving and Measuring Multifunctionality of Rural Space: A Study of Suzhou, China

“…Things are quite different in Jishan, a village located on the outskirts of urban areas, rural area is mainly dominated by construction space, and the combined ratio of town, village, and road is as high as 80.55%. The real-time Tencent user quantity (RTUQ) data is a type of LBS data provided by Tencent Company; it contains real-time numbers of mobile device users who use Tencent applications, such as Tencent Mobile App QQ, WeChat, and other mobile applications that provide location-based service using GPS devices with a spatial accuracy level of~10 m [24,52]. Unlike old-fashioned mobile phone position data with a spatial resolution of~100 m to 300 m, due to the service coverage of cell towers defined by Voronoi tessellations according to related studies [53,54], the RTUQ data has higher accuracy to record and collect user's position in a relatively small-scale area.…”

“…The last two decades has witnessed the rapid development of GIS, which prominently promoted new methods of collecting spatial-temporal data, managing behavior data and representing human activity patterns [21,22]. Further, recent emergence of geographic big data, e.g., location-aware technologies (LAT) data [23] and location-based services (LBS) data [24], has created an emerging research stream, especially in interdisciplinary fields of big data and human geography including, in particular, urban computing and social sensing [25][26][27], which offers a new opportunity for human geography study within multi-scales. For example, mobile phone signaling data [28,29], smart card of bus/metro data, and taxi GPS trajectory data [30,31] are used to explore mobility patterns on macro-scale, social media data, POI data [32,33], and Google Maps [34,35] are new-style tools for vitality assessment of activities on micro-scale such as in a community level.…”