A context-sensitive correlated random walk: a new simulation model for movement

ABSTRACT

Computational Movement Analysis focuses on the characterization of the trajectory of individuals across space and time. Various analytic techniques, including but not limited to random walks, Brownian motion models, and step selection functions have been used for modeling movement. These fall under the rubric of signal models which are divided into deterministic and stochastic models. The difficulty of applying these models to the movement of dynamic objects (e.g. animals, humans, vehicles) is that the spatiotemporal signal produced by their trajectories a complex composite that is influenced by the Geography through which they move (i.e. the network or the physiography of the terrain), their behavioral state (i.e. hungry, going to work, shopping, tourism, etc.), and their interactions with other individuals. This signal reflects multiple scales of behavior from the local choices to the global objectives that drive movement. In this research, we propose a stochastic simulation model that incorporates contextual factors (i.e. environmental conditions) that affect local choices along its movement trajectory. We show how actual global positioning systems observations can be used to parameterize movement and validate movement models and argue that incorporating context is essential in modeling movement.

KEYWORDS:

• Movement model
• stochastic models
• agent-based simulation
• environmental context
• behavior
• movement pattern
• scale
• tiger

View correction statement:

Correction to: Sean Ahearn, A context-sensitive correlated random walk: a new simulation model for movement

Acknowledgements

S. Dodge and G. Xavier’s work was supported under the 2015 UCCS Committee on Research and Creative Works (CRCW) and the UCCS College of Letters, Arts, and Sciences Student-Faculty Research Awards. We thank Saksit Simcharoen, Somphot Duangchantrasiri, Somporn Pakpein, Onsa Norasarn for assistance in the field. The Thai Olympic Fibre-Cement Co., Ltd. and the USFWS Tiger Rhinoceros Fund funded the tiger research. The authors wish to thank the reviewers for their insightful and constructive comments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The Thai Olympic Fibre-Cement Co., Ltd. and the USFWS Tiger Rhinoceros Fund funded the tiger research.