ALBERT

Description: Understanding human mobility patterns provides us with knowledge about human mobility in an urban context, which plays a critical role in urban planning, traffic management and the spread of disease. Recently, the availability of large-scale human-sensing datasets enables us to analyze human mobility patterns and the relationships between humans and their living environments on an unprecedented spatial and temporal scale to improve decision-making regarding the quality of life of citizens. This study aims to characterize the urban spatial-temporal dynamic from the perspective of human mobility hotspots by using mobile phone location data. We propose a workflow to identify human convergent and dispersive hotspots that represent the status of human mobility in local areas and group these hotspots into different classes according to clustering their temporal signatures. To illustrate our proposed approach, a case study of Shenzhen, China, has been conducted. Six typical spatial-temporal patterns in the city are identified and discussed by combining the spatial distribution of these identified patterns with urban functional areas. The findings enable us to understand the human dynamics in a different area of the city, which can serve as a reference for urban planning and traffic management.

Description: IJGI, Vol. 7, Pages 320: Exploring Railway Network Dynamics in China from 2008 to 2017 ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7080320 Authors: Yaping Huang Shiwei Lu Xiping Yang Zhiyuan Zhao China’s high speed rail (HSR) network has been rapidly constructed and developed during the past 10 years. However, few studies have reported the spatiotemporal changes of railway network structures and how those structures have been affected by the operation of high speed rail systems in different periods. This paper analyzes the evolving network characteristics of China’s railway network during each of the four main stages of HSR development over a 10-year period. These four stages include Stage 1, when no HSR was in place prior to August 2008; Stage 2, when several HSR lines were put into operation between August 2008, and July 2011; Stage 3, when the network skeleton of most main HSR lines was put into place. This covered the period until January 2013. Finally, Stage 4 covers the deep intensification of several new HSR lines and the rapid development of intercity-HSR railway lines between January 2013, and July 2017. This paper presents a detailed analysis of the timetable-based statistical properties of China’s railway network, as well as the spatiotemporal patterns of the more than 2700 stations that have been affected by the opening of HSR lines and the corresponding policy changes. Generally, we find that the distribution of both degrees and strengths are characterized by scale-free patterns. In addition, the decreasing average path length and increasing network clustering coefficient indicate that the small world characteristic is more significant in the evolution of China’s railway network. Correlations between different network indices are explored, in order to further investigate the dynamics of China’s railway system. Overall, our study offers a new approach for assessing the growth and evolution of a real railway network based on train timetables. Our study can also be referenced by policymakers looking to adjust HSR operations and plan future HSR routes.

Description: China’s high speed rail (HSR) network has been rapidly constructed and developed during the past 10 years. However, few studies have reported the spatiotemporal changes of railway network structures and how those structures have been affected by the operation of high speed rail systems in different periods. This paper analyzes the evolving network characteristics of China’s railway network during each of the four main stages of HSR development over a 10-year period. These four stages include Stage 1, when no HSR was in place prior to August 2008; Stage 2, when several HSR lines were put into operation between August 2008, and July 2011; Stage 3, when the network skeleton of most main HSR lines was put into place. This covered the period until January 2013. Finally, Stage 4 covers the deep intensification of several new HSR lines and the rapid development of intercity-HSR railway lines between January 2013, and July 2017. This paper presents a detailed analysis of the timetable-based statistical properties of China’s railway network, as well as the spatiotemporal patterns of the more than 2700 stations that have been affected by the opening of HSR lines and the corresponding policy changes. Generally, we find that the distribution of both degrees and strengths are characterized by scale-free patterns. In addition, the decreasing average path length and increasing network clustering coefficient indicate that the small world characteristic is more significant in the evolution of China’s railway network. Correlations between different network indices are explored, in order to further investigate the dynamics of China’s railway system. Overall, our study offers a new approach for assessing the growth and evolution of a real railway network based on train timetables. Our study can also be referenced by policymakers looking to adjust HSR operations and plan future HSR routes.