I thought Sarkar et al.’s “Analyzing Animal Movement Characteristics From Location Data” (2014) was super interesting, as I don’t have a very strong background in environment and I didn’t know about all of the statistical methods involved in understanding migratory patterns via GPS tracking. The visualizations were super interesting, like the Rose diagram to show directionality and the Periodica method to then determine hotspots. I also appreciated the macroscopic viewpoint of this article; though the inclusion of equations is important for replication and critical understanding, it is also important to discuss the outputs and limitations of the equations at a larger level, in order to better understand results. It is especially useful for those without deep math backgrounds, like myself, to understand the intentions of using these certain equations without having the math background of being able to visualize output.

As interesting as it was to learn about the incredible utility of understanding migratory patterns of animals, I couldn’t help but think about applications to human geography. I wonder if these patterns are already being used to extrapolate information on someone based on their location, as the Toch et al. (2010) paper on privacy for this week hinted at. If they are different, it would be interesting to evaluate the utility of the methods to study human spatial data patterns as applied to animal migratory patterns. Since Sarkar et al. used unsupervised classification to learn new patterns, it seems like the combination of methods used could apply (and probably do apply) to human spatial data mining. As terrifying as that is.