This paper by Laube and Purges (2011) truly brings together so many of the concepts that we have explored in class over the last couple weeks: scale (spatial, temporal), temporal GIS and error and uncertainty. In fact, this article addresses Noe’s concerns from last week about temporal scale following his summer research work. What a way to tie up the course!
This article presents a thoughtful (and alliteration heavy) list of problems in movement analysis, but focuses on “granularity grief” (2), which is the problem of temporal scale in movement analysis. My one criticism of the article is the repetition: I am not sure if they were short on words, but it felt like the article’s focus (gap in research, lack of scale research, movement parameters, etc…) were stated too often. That being said, I found the discussion very thoughtful, especially the fact that when it comes to temporal scales “the common assumption ‘the finer, the better’ does not hold” (15). They explain that in case of moving cows, this is because of the limitations of the uncertainty in the movement. This is interesting, as it is drilled into scientists that ‘more data is better data’, but obviously, this is not always the case, and it is important to take into account the other limitations of the study. This is an important concept to retain in GIScience, where so much data is “big data”. Maybe somebody should share this notion with the cell phone makers/service providers/app developers so that they collect less of our personal/private data!