Are We Certain that Uncertainty is the Problem?

Unwin‘s 1995 paper on uncertainty in GIS was a solid overview of some of the issues with data representation that might fly under the radar or be assumed without further comment in day-to-day analysis.  He discussed vector (or object) and raster (or field) data representations, and the underlying error inherent in the formats themselves, rather than the data, per se.

While the paper itself is clear and fairly thorough, I can’t help but question whether error and uncertainty are worth fretting over. Of course there is error, and there will always be error in a digital representation of a real-world phenomenon. Those people, such as scientists and policy makers, who rely on GIS outputs, are not oblivious to these representation flaws. For instance, raster data is constrained by resolution. It is foolhardy to assume that the land cover in every inch of a 30-meter grid cell is exactly uniform. It is also wrong to suggest that some highly mobile data (like a flu outbreak) would remain stationary over the course of the interval between sensing/mapping. There are ways around this, such as spatial and temporal interpolation algorithms and other spatial statistics, and I feel like estimates are often sufficient. If they aren’t, then perhaps the problem isn’t with the GIS, but rather in the data collection. Better data collection techniques, perhaps involving more remote sensing (physical geography) or closer fieldwork (social geography) would go far in lessening error and uncertainty.

With all of that said, I am not about to suggest that GIS is perfect. There is always room for growth and improvement. But, after all, the ultimate purpose of visualizing data is for understanding and gaining a mental picture of what is happening in the real world. An error-free or completely “certain” data representation is not only impossible within human limitations, but it is not particular necessary.

– JMonterey

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