Movement GIS and Cows (Laube and Purves, 2011)

What a cross-sub-disciplinary article! In their efforts to address temporal scale issues with regard to movement data, Laube and Purves (2011) nicely tie together many of the GIScience topics that we have covered in this course.

This article reaffirms my view of movement GIS as a subdomain of temporal GIS. Broadly, temporal GIS looks to integrate time into spatial analyses, and movement is an excellent example of where this needs to be done. Moreover, movement is directly connected to many of the theories and implementation strategies behind time geography. Laube and Purves’ research on cows’ movement patterns nicely reflects the interconnectedness between space and time, which is a foundational idea behind time geography. While I understand that the scope of this paper might not have allowed for it, I would have liked to see more references to temporal GIS and time geography literature.

It is interesting to think about the tension between the conceptual simplicity of movement data and the practical complexity of extracting meaningful knowledge from such data. As in this case, movement can often be represented by a series of points, each with an ID, a timestamp, and a set of coordinates. Each point represents a static state of an entity and movement can be inferred by combining points to form a trajectory. This reflects a significant source of uncertainty, as the Euclidean distance between two points may not be an accurate depiction of the movement that took place (which was nicely pointed out in this article). Furthermore, analyzing movement patterns to learn about meaningful behaviours is challenging as many behaviours (like cows grazing) take place at one space over time. This paper’s focus on “granularity grief” also nicely reminds us that behaviours are dependent on temporal scale.

With the popularity of data sources from things like location-based services and social media, we are flooded with movement data at incredibly high spatial and temporal granularities. I think that the field of movement analysis will be an incredibly important direction for future research in GISciences.

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