Dataset of origin and destination pairs in street networks, for the evaluation of the Earth Mover's Distance as a metric of alignment
This dataset was created as part of my PhD Project at the Department of Computing Science investigating how map readers perceive the complexity of routes displayed on a digital map. As part of my PhD project, I have conducted two experiments where participants have been asked to judge the complexity of different routes and describe what made them look more complex. Some of the routes that the participants were shown were in grid-like street networks, and when describing why these routes look complex, they sometimes described the routes as either aligned or misaligned. As an example, a path can be described as to follow the street, if the destination is oriented in alignment with the primary orientations in the street network; and it can be said to cross the river, or to cross the street, if the orientation is misaligned. This triggered an investigation into how the alignment between the orientation of the origin and destination of a route with(in) how the streets are oriented in the surrounding street network. The primary dataset contains 79,987 Origin and Destination pairs (OD-pair) that have been sampled from five locations in 100 different cities to evaluate the Earth Mover's Distance (EMD) between circular distributions as a metric of alignment. Where a higher EMD is indicative of a higher degree of misalignment between the orientations. The dataset was used to test whether a higher EMD is predictive of longer and more complex routes, and compare it to other predictors including properties of the street network that earlier research have identied as sources of route complexity.
Krantz-Horned, A., Falomir, Z., and Richter, K.-F. (2025). Measuring Alignment with the Grid: Evaluating the Earth Mover’s Distance as a Metric of Alignment between Orientations. Submitted manuscript.
The dataset is created with data provided by OpenStreetMap under the Open Database License.
Department of Computing Science at Umeå University
[GEMET] An organized collection of computer hardware, software, geographic data, and personnel designed to efficiently capture, store, update, manipulate, analyze, and display all forms of geographically referenced information that can be drawn from different sources, both statistical and mapped.