Biologically Accurate Simulation of Bee Polarisation Vision for Navigation

5.2 GB of simulation data models polarisation vision in honeybees and bumblebees. The dataset, created by George Kolyfetis and last updated in May 2026, incorporates species-specific dorsal rim area anatomy and real sky polarisation images. It evaluates navigational accuracy under matched filter and vector-sum models, with errors below 5° and median errors of ~10° and ~30° respectively.

Use Cases

• Compare navigational model performance based on simulated polarisation perception.
• Study the impact of dorsal rim area anatomy on navigation accuracy based on species-specific parameters.
• Generate testable predictions for insect navigation under natural sky conditions based on the mechanistic framework.
• Analyze the relationship between sun elevation and estimation error based on the simulation results.

Strengths

• Simulation incorporates biologically realistic parameters, including species-specific ommatidial optical axis directions and microvillar orientations.
• Evaluates two distinct navigational models (matched filter and vector-sum) across sun elevations.
• Based on real sky polarisation images to capture natural skylight properties.
• Dataset size is 5.2 GB, indicating a medium-scale simulation.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific simulation parameters and sky images used.

Provenance

Source

George Kolyfetis via figshare

Collection Method

Computational simulation incorporating anatomical data and real sky images.

Freshness

Last updated 2026-05-28 15:40:18; freshness should be verified.