First off, I realize that this is perhaps not the most stackexchange-esque question. I am however having trouble finding a good source of information for this. So if there is a better place for me to look for this information please redirect me there.
I am creating an application for which the persistence layer is PostGIS, and I am unsure what if any projection I should use for storing my data.
My spatial data system is working on the following general requirements:
- The data that I am storing pertain to events, and I would like to be able to find events that are nearby another event. This is to say, given event 'foo' I would like to find events within a certain radius of 'foo.'
- The data points are distributed at a national, and later at a potentially global level, but the distance comparisons would only occur at a relatively local level < 100k, so I only really care about fidelity of distance up until that point.
- Accuracy is much less important than speed in my use case, and single digit percentage error is acceptable as long as the distance lookup is quick.
I have looked up the geography type which is not tied to a particular position, however the PostGIS documentation appears to take a rather condescending view of the geography type:
If you don't understand projections, and you don't want to learn about them, and you're prepared to accept the limitations in functionality available in GEOGRAPHY, then it might be easier for you to use GEOGRAPHY than GEOMETRY. Simply load your data up as longitude/latitude and go from there.
I am relatively comfortable with the mathematical notion of projection and the topology of manifolds, and I do care about performance, but I have little GIS specific knowledge and I have yet to find a place where there is a mapping between SRIDs and usecases. Is there a specific type of projection that I should be using, or a type that I should be looking for?