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China is experiencing massive rural-urban migration. The departure of young adults from rural areas poses challenges to traditional old age support arrangements in rural China. Concerning the practice of Confucian filial piety within the context of rural-urban migration, this study aims to explore the extent and dynamics of support among migrant workers' older parents in rural China. By employing a qualitative approach, this study carried out 29 semi-structured interviews in two rural villages and revealed the changing nature of filial piety in modern rural China in the context of rural-urban migration. First, it found that in the wake of rural adult children's migration, an increasing number of rural older parents have begun to spend their old age co-residing with their migrant children in cities. Second, the study reshapes our understanding of the relationship between the land and rural older people's need for physical support. Besides, the study casts light on rural older parents' help-seeking behaviour, revealing the dynamics of their efforts to seek support both from their families and their local communities. findings provide insights for policy makers into ways of improving rural older people's well-being. Further, given China's special social and economic characteristics, this study contributes to enhancing our understanding of support for older people in the context of children's immigration.

The normal flow of traffic is impeded by abnormal events and the impacts of the events extend over time and space. In recent years, with the rapid growth of multi-source data, traffic researchers seek to leverage those data to identify the spatial-temporal dynamics of traffic flow and proactively manage abnormal traffic conditions. However, the characteristics of data collected by different techniques have not been fully understood. To this end, this study presents a series of studies to provide insight to data from different sources and to dynamically detect real-time traffic states utilizing those data. Speed is one of the three traffic fundamental parameters in traffic flow theory that describe traffic flow states. While the speed collection techniques evolve over the past decades, the average speed calculation method has not been updated. The first section of this study pointed out the traditional harmonic mean-based average speed calculation method can produce erroneous results for probe-based data. A new speed calculation method based on the fundamental definition was proposed instead. The second section evaluated the spatial-temporal accuracy of a different type of crowdsourced data - crowdsourced user reports and revealed Waze user behavior. Based on the evaluation results, a traffic detection system was developed to support the dynamic detection of incidents and traffic queues. A critical problem with current automatic incident detection algorithms (AIDs) which limits their application in practice is their heavy calibration requirements. The third section solved this problem by proposing a selfevaluation module that determines the occurrence of traffic incidents and serves as an autocalibration procedure. Following the incident detection, the fourth section proposed a clustering algorithm to detect the spatial-temporal movements of congestion by clustering crowdsource reports. This study contributes to the understanding of fundamental parameters and expands the knowledge of multi-source data. It has implications for future speed, flow, and density calculation with data collection technique advancements. Additionally, the proposed dynamic algorithms allow the system to run automatically with minimum human intervention thus promote the intelligence of the traffic operation system. The algorithms not only apply to incident and queue detection but also apply to a variety of detection systems.