Trajectory analysis

suggested by: Gudrun Wallentin

Background 

This spatial data science project works with a large GPS dataset of >60,000 cattle locations that were collected over four years on a pasture close to Salzburg. The data is modelled in a postgres database. However, before it can be used for analysis it needs to be pre-processed, checked for validity, and complemented with further relevant variables.

Short description

This thesis aims to analyse social movement of cattle on a pasture by means of the MovingPandas python library, developed by Anita Graser. The main analytical focus is to evaluate, how separate trajectories related to each other. Beyond the analysis of interaction, the cattle's location shall be correlated with potential predictors like time of the day, elevation, land cover, weather, vegetation intensity, proximity to water, or the seasonal state.

 

Suggested reading

MovingPandas repository: https://anitagraser.github.io/movingpandas/ 

Start

anytime

Prerequsites/qualification
Interest in the topic. On-site involvement in the revitalisation activities isn't necessary, but possible and highly welcome.

Spatial ABMs

 suggested by: Gudrun Wallentin 

Background
Although agent-based modelling per definition is spatially explicit, the inherent potential of spatial concepts has not been fully exploited. Usually the modelled system is represented by individual agents that are related by circular buffers, rather than by more realistic spatial representations of interaction areas like vision cones or viewsheds in heterogeneous environments.

Short description

This rather conceptual thesis takes a systematic look into the question how spatial configuration structures a system. It analyses whether and how the explicit consideration of space impacts typical emergent phenomena like flocking of social animals or oscillations in populations.

Suggested reading

Manson, S., An, L., Clarke, K. C., Heppenstall, A., Koch, J., Krzyzanowski, B., ... & Tesfatsion, L. (2020). Methodological issues of spatial agent-based models. Journal of Artificial Societies and Social Simulation, 23(1).

Wallentin, G. (2024) Spatial Simulation eBook, Lessons 7 "Agent-based Modelling" and 8 "Movement"

Start

anytime

Prerequsites/qualification
Interest in the topic. Successful completion of the course "Spatial Simulation" is recommended.

Virtual pasture ABM

suggested by: Gudrun Wallentin

Background 

This research accompanies the revitalisation of a traditional alpine cattle pasture “Vierkaseralm” on Untersberg near Salzburg City. The study area was abandoned by the last farmer in 1958, since then shrubs (mainly Pinus mugo) have encroached the former grasslands. In summer 2021 the pasture was revived, the cattle got GPS devices and the area was scanned with a UAV. The data that have been collected in the past four years provide a unique opportunity for scientific monitoring of pasture revitalisation.

Short description

This thesis aims to apply an existing agent-based model of cattle-grassland interaction to the Vierkaseralm. The model will be calibrated with the existing GPS data of the cattle and other available datasets in a pattern-oriented modelling approach, using data-driven optimisation paradigms such as genetic algorithms. The 2024 data will be used for model validation and to evaluate the approach.

 

Suggested reading

Wallentin (2024) "Spatial Simulation" eBook

Start

anytime

Prerequsites/qualification
Interest in the topic. On-site involvement in the revitalisation activities is possible and highly welcome.