HCGRAug 1, 2019

Visualising Geographically-Embedded Origin-Destination Flows: in 2D and immersive environments

arXiv:1908.00662v22 citations
AI Analysis

This work addresses the challenge of effectively representing flow data on maps for users in fields like geography or data analysis, but it appears incremental as it builds on existing flow visualization methods.

The thesis tackled the problem of visualizing geographically-embedded origin-destination flows, such as people or trade movements, by developing novel techniques for both 2D and immersive environments and evaluating them through controlled user studies.

This thesis develops and evaluates effective techniques for visualisation of flows (e.g. of people, trade, knowledge) between places on geographic maps. This geographically-embedded flow data contains information about geographic locations, and flows from origin locations to destination locations. We explored the design space of OD flow visualisation in both 2D and immersive environments. We do so by creating novel OD flow visualisations in both environments, and then conducting controlled user studies to evaluate different designs.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes