Note on the source. This source should be read with caution: it may be funded by the sector, a draft or a thesis, or rely on self-reported or modelled data. See the limitations below.
The question
What visit profiles emerge when cruise passengers' GPS trajectories in Visby are grouped by spatial similarity, and how are stops distributed across the different groups?
The method
GPS tracks (recorded every 5 seconds) of cruise passengers collected in summer 2018 and 2019: 408 initial tracks, 267 used within 3.5 km of the port. Stop detection with DBSCAN (minimum 2 minutes), trajectory similarity with dynamic time warping and hierarchical clustering; maps in ArcGIS.
What the study finds
- Ships usually arrive between 7 and 9 am, while many Swedish shops open at 10, so early on visitors pass through areas where businesses are still closed. The author suggests this may spread spending unevenly, though spending was not measured.
- The tracks suggest some visitors took a bus into the historic core; they spent more time in the less-visited northern areas. In the author's view, placing drop-off points inside the core could ease crowding in the central and southern areas.
For a small historic town, knowing where cruise visitors stop and for how long helps decide where to put services, alternative routes and bus drop-off points. The thesis also notes that ships arrive before many shops open, something to consider when aligning call times with the town's hours.
Limitations
A degree thesis with no statistical tests on differences between clusters (small, unbalanced groups) and no questionnaire or spending data; results depend on many parameters chosen in advance, and the clusters are not very distinct from one another.
Borg, P. (2023). Segmenting cruise passengers based on their spatio-temporal similarity - an approach utilising dynamic time warping. Uppsala universitet, Kulturgeografiska institutionen (serie Uppsatser).
Summary written by the ODYBOAT Observatory in our own words. Tables and figures belong to the authors.