Coarse grained data issues low resource settings

Despite Goodchild et al.’s (1998) article’s technical components, the article did make me think of uncertainty regarding boundaries and course grained satellite imagery. Exploring low resource settings on Google Earth is one such example. Although an incomplete geolibrary, I consider Google Earth to be effective in its user friendly interface and features (layers and photographs), and of course, ubiquity. It’s a start. With this in mind, ‘flying’ over towns in Colombia on Google Earth, and the terrible, terrible satellite imagery that was available. (The low quality imagery remains unchanged since the last time I checked it half a year ago). One of the towns/districts is Puerto Gaitan. How do we account for the lack of resources given to collecting fine grained even medium grained visualizations?

According to Goodchild et al., alternative methods for displaying fuzzy regions must be applied where cartographic techniques are not enough. “A dashed region boundary would be easy to draw, but it would not communicate the amount of positional uncertainty or anything about the form of the z(X) surface” (208). What do we do then, when the data cannot even be analyzed because it is too coarse? For low resource settings, we are just going back to where we started. No financial incentives to improve data (from coarse to fine) = continuation of coarse grained data = poor visualization = cannot be utilized in studies = no advancements in research are made = back to the start, no financial incentives to improve the quality of data. How do we break this cycle?

-henry miller

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