Atkinson and Tate provide a thorough overview of geostatistical issues and their solutions in this piece. Although the authors do make a point of simplifying concepts, I still had to read the article a few times to really understand what was happening. I would have greatly benefited from more examples to illustrate their points, or maybe one that was a bit simpler than the one they chose. Despite my difficulties in grasping everything that was said in the article on my first read, I believe this article to be an important starting point for those embarking on research where scale plays a major role. For instance, knowing about the smoothing problem when performing kriging analyses (and that the variance lost through smoothing can be estimated by subtraction) could be the difference between a successful project and an unsuccessful one.
Some things I can’t help but wonder after reading this piece are:
What has changed in the literature since this was published in November 2000?
Is there now a solution to the covariance problem (ie that it varies unpredictably between the original and kriged data)?
This article made me think more about how scale can relate to my own project for this course, and what issues to avoid in my own research. I’ll be sure to look at more literature concerning the interaction of scale and VGI moving forward. Overall, I found this piece to be a solid overview of geostatistical problems and solutions.