In this paper we present a time-aware, density-based clustering technique for the identi cation of stay regions in trajectories of low-sampling-rate GPS points, and its application to the study of animal migrations. A stay region is de ned as a portion of space which generally does not designate a precise geographical entity and where an object is signi cantly present for a period of time, in spite of relatively short periods of absence. Stay regions can delimit for example the residence of animals, i.e. the home-range. The proposed technique enables the extraction of stay regions represented by dense and temporally disjoint sub-trajectories, through the speci cation of a small set of parameters related to density and presence. While this work takes inspiration from the eld of animal ecology, we argue that the approach can be of more general concern and used in perspective in different domains, e.g. the study of human mobility over large temporal scales. We experiment with the approach on a case study, regarding the seasonal migration of a group of roe deer.

Extracting stay regions with uncertain boundaries from GPS trajectories : a case study in animal ecology / M.L. Damiani, H. Issa, F. Cagnacci - In: Proceedings ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems / [a cura di] I. Cruz. - [s.l] : ACM, 2014. - ISBN 9781450316910. [10.1145/2666310.2666417]

Extracting stay regions with uncertain boundaries from GPS trajectories : a case study in animal ecology

M.L. Damiani;H. Issa;
2014

Abstract

In this paper we present a time-aware, density-based clustering technique for the identi cation of stay regions in trajectories of low-sampling-rate GPS points, and its application to the study of animal migrations. A stay region is de ned as a portion of space which generally does not designate a precise geographical entity and where an object is signi cantly present for a period of time, in spite of relatively short periods of absence. Stay regions can delimit for example the residence of animals, i.e. the home-range. The proposed technique enables the extraction of stay regions represented by dense and temporally disjoint sub-trajectories, through the speci cation of a small set of parameters related to density and presence. While this work takes inspiration from the eld of animal ecology, we argue that the approach can be of more general concern and used in perspective in different domains, e.g. the study of human mobility over large temporal scales. We experiment with the approach on a case study, regarding the seasonal migration of a group of roe deer.
data mining; spatio-temporal data; migrations; animal ecology; clustering; mobility patterns
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/247452
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