Quote from a paper I recently submitted: "As movement is arguably the most significant way by which animals respond to changes in their surrounding environment, it can serve as an instrument for environmental response and understanding movement can elucidate the relations between environmental drivers of animal behavior and demography (Eikelboom et al., 2020; Nathan et al., 2008)."
In this project, I would like to vividly visualize how animals interact with the surrounding environment (i.e., how environmental variables might influence the movement path selection) using the turkey vulture migration example.

The raw tracking datasets and environmental annotations were obtained from Movebank (Bildstein et al., 2021) The tracking dataset was preprocessed and clustered to obtain the dataset for this visualization. As the paper is not yet published, I cannot share the codes for preprocessing or clustering. But the datasets after those steps (attached) are as follows:

Environment sample dataset: a series of systematically sampled points, each with a series of environmental variables corresponding to that location.
(17112 sample points in total)

Turkey vulture dataset: tracking points recorded.
(16402 tracking points in total)

The core idea is to visualize trajectories on top of environmental variables. I found some examples online.

1. Daniel Shiffman Smoke particle system



2. Braun, E., Düpmeier, C., Mirbach, S., & Lang, U. (2017, May). 3D Volume Visualization of Environmental Data in the Web. In International Symposium on Environmental Software Systems (pp. 457-469). Springer, Cham.

I experimented on multiple ways to visualize the environmental variables, such as smoke and terrain

Finalluy, I decided to use multiple terrains, each representing one environmental variable. There are three buttons and three sliders. The three buttons control the coloring of the terrains, visualizing the trajectory lines and tracking points, respectively. The three sliders control the fluctuation of the terrain, the vertical distance between terrains and base z coordinates of terrains. With the three sliders, one can analyze the tracking data with each of the environmental variables.

All work is developed within Processing
Wan_TrajectoryEnvironment.zip