Problems of Scale in GIScience

The topic of scale is a good example of GIS being synonymous with “doing science”. When I think about GIScience as opposed to GIS, I think about the problems that arise when trying to represent and communicate space using digital geographic information. Scale, as expressed in Spatial Scale Problems and Geostatistical Solutions: A Review by Atkinson and Tate, presents many problems for how to optimally relate and represent spatial features and properties. GIS is special because unlike traditional graphical maps, they have the capacity to integrate multi-scale data. Therefore, when discussing spatial data, one must address issues of scale and the implications theses new types of interfaces have for representing and analyzing spatial data.

Scale is very much a central topic of spatial cognition. I have seen many applications of scale for explaining how we conceptualize and categorize space. Atkinson and Tate assert in their paper that, “one can never observe “reality” independent of some sampling framework, so that what we observe is always a filtered version of reality” (Atkinson and Tate, 2000). This acknowledgement of the conceptual frameworks that contextualize scale is an essential part of cognitive processes that involve spatial properties as a core component.

In addition, scale is a fundamental component of spatial statistics and analysis. MUAP and variations of sampling schemes are met with issues pertaining to scale. In our final project for Geog 308, my group members and I have to address issues of scale in our analysis. In order to observe urban sprawl over time for the city of Maceio, Brazil, we have to confront problems of spatial resolution and how to stratify and randomly choose our ground truth sample points. The scales of these samples affect the heterogeneity of land cover classes and affect the results of our analysis.

In addition, I find that scale is relevant to the other topic being presented tomorrow on the sharing economy in GIScience. Scale is very important when discussing networks, accountability, and trust within the sharing economy. I hope to discuss this topic further during tomorrow’s discussion period.


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