If you are going to go that far, then you might as well not use the naive normal distribution for the location. See the following two articles if you would like to understand why:
Guo Q., Y. Liu, and J. Wieczorek. 2008. Georeferencing locality descriptions and computing associated uncertainty using a probabilistic approach. International Journal of Geographical Information Science, Vol. 22, No. 10., pp. 1067-1090.
Liu Y., Q.H. Guo, J. Wieczorek, and M.J. Goodchild. 2009. Positioning localities based on spatial assertions. International Journal of Geographical Information Science, Vol. 23, No. 11., pp. 1471-1501.
On Tue, Mar 1, 2011 at 5:40 PM, Paul Murray pmurray@anbg.gov.au wrote:
On 27/02/2011, at 6:01 AM, Bob Morris wrote:
"Note: The number of digits of the values in <coordinates> MUST NOT be interpreted as an indication to the level of uncertainty." The section following is also interesting, albeit irrelevant for your procedure. It implies that when uncertainty is omitted (and therefore unknown), then "geo:41.53000000,-70.67000000" and "geo:41.53,-70.67" identify the same geo resource.
This follows from the definition of xs:float, which RDF (and presumably geo) borrow. These two strings are each representations of the same IEEE floating-point value. Something with a precision is a different datatype. It seems to me that georeferencing needs a notion of density - some way to express a location as a value at a point and a standard deviation (we assume a normal distribution). A rectangle becomes an integral of these densities at each point - standard deviation of zero corresponding to the usual sharply-defined rectangle. You'd probably also want to supply a cutoff value. _______________________________________________
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