Animal Movement Characteristics from Location Data, Sarkar et al. (2014)

Sarkar et al. (2014) present an analytical framework for making inferences about animal movement patterns from locational information. The article was an insightful show-don’t-tell introduction to how movement research could be applied beyond the domain of GIScience. Also, I think this may be one of the first articles we’ve looked at with an explicitly ecological application of GIScience research… A welcome addition!

It’s becoming increasingly evident how these GIScience topics we’ve discussed in class interact to provide a better understanding of how geospatial information is analyzed and represented. I appreciated the authors’ discussion of uncertainty in the Li et al. (2010) algorithm for detecting periodicity. I found myself tempted again to assume that increasing temporal resolution is the best way to minimize this sort of uncertainty. Even withholding concerns for feasibility, ultimately I’m not convinced that this really does more than mask the problem. The detection of periodicity through cluster analysis resembles aggregation techniques for reducing the influence of outliers on uncertainty in the resulting periods, but I am still a little unclear on how the temporality of the location data was incorporated into the clusters. Does the Fourier analysis account for points near in space but distance in time? Perhaps the assumption of linearity is enough in the assessment of migration patterns.

The distinction between directionality and periodicity as components of movement was insightful. Typically I would think about the significance of movement as it relates to the physical space, but Sarkar et al. demonstrate how inferences from orientation and temporality of movement can be insightful on their own.

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