Thoughts on “Approaches to Uncertainty in Spatial Data”

This chapter deals with a number of aspects of uncertainty in spatial data. The one that caught my eye in particular is definition: how well defined or not well defined a geographical object is. Well defined objects tend to be human made (like census tracts), while poorly defined objects tend to be natural (like a patch of woodland). This raised a question for me that this chapter does not address: how should or can someone deal with objects that may be overlapping/related if one is well defined and the other isn’t? For example, would performing an intersect on two such object be appropriate, considering the gap in the quality of definition? Does a large difference in definition make two objects incomparable? Maybe not, and that is why the paper does not address this particular issue. However, I would say there could be issues in data incompatability between a well defined and poorly defined object. For example, if there is a well-defined census tract overlaid on a poorly defined patch of woods, how well could the intersect between the two be defined? This perhaps feeds into other issues of uncertainty mentioned in the chapter, like vagueness and error. But fundamentally, I would say that such a notable difference in definition would make these object incompatible. Perhaps one data type could be converted, for example the wood patch could be converted and given “hard” borders under the assumption that these are clearly defined, even if they aren’t. Even so, however, this overlooks the central properties of the object and may not bridge the gap between the level of definition in each object.

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