Proximity-Based Aggregation Method for LBS Human Mobility Data

Abstract

Human mobility is an inevitable element of urban development. The rise of big data has accelerated the popularity of various location-based service (LBS) data, and mobility data has gradually become the mainstream data. When mobility data is applied to the research into human mobility, geographic location will be integrated into a complex network structure composed of massive human mobility data to form a geographic network space, which will integrate human mobility and urban development in the era of big data. Mobility data features large quantity, complexity and redundancy, and its aggregation is valuable. In this paper, based on LBS human mobility data, a geographic proximity-based aggregation method for mobility data is proposed, aiming at aggregating mobility data of geographic proximity according to human mobility values to achieve mobility data aggregation in geographic sense without changing the situation of data, and generate a series of urban aggregation areas formed by closely approximate internal mobility data.