Where were you? Development of a time-geographic approach for activity destination re-construction

摘要: Abstract With the use of individual-level travel survey datasets describing detailed activities households, it is possible to analyze human movements with a high degree precision. However, data are not without quality issues. Potential exists for origins and destinations reported trips be geo-referenced, perhaps due misreported information or inconsistencies in spatial address databases, which can limit usefulness data. From an analytical standpoint, this serious problem because single unreferenced stop trip record effect renders that individual’s useless, especially cases where analyzing chains activity locations interest. This paper presents framework basic computational approach exploring unlocatable inherent surveys. Derived from recent work developing network-based, probabilistic time geography, proposed methods able estimate likely missing destinations. The generate potential path trees used visualize quantify demonstrated simulated smaller metropolitan area.