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I see MerseyViking has recommended a quadtree. I was going to suggest the same thing and in order to explain it, here's the code and an example. The code is written in R but ought to port easily to, say, Python. The idea is remarkably simple: split the points approximately in half in the x-direction, then recursively split the two halves along the ...


See if this algorithm gives enough anonymity for your data sample: start with a regular grid if polygon has less than threshold, merge with neighbor alternating (E, S, W, N) spiraling clockwise. if polygon has less than threshold, go to 2, else go to next polygon For example, if the minimum threshold is 3:


Similarly to Paulo's interesting solution, how about using a quad tree subdivision algorithm? Set the depth you would like the quadtree to go to. You could also have a minimum or maximum number of points per cell so some nodes would be deeper/smaller than others. Subdivide your world, discarding empty nodes. Rinse and repeat until the criteria are met.


I am not a Java developer and don't know of any existing Java implementations for this, but using the k-Nearest Neighbors algorithm with a k-d tree will likely give much better performance. However, if accuracy is important, you will need to implement the Haversine (spherical) or Vincenty (ellipsoidal) distance formulae for the distance metric, since ...


What you're trying to do doesn't really make sense. Quadtree.query works by intersecting the extents of the elements with a rectangular extent. It's up to you to further filter them. However, you can use the overloaded version of query with a subclass of ItemVisitor to achieve what you want. public class QtreeTest { public static class HoleVisitor ...


There are several benefits to geohash over quadkey: cross language support. geohash has open source implementations in a number of languages (c, java, python, ruby, perl, javascript). If you need external contributors to connect with your quadtree based data, you gain maximum flexibility with geohash. If you are using python, there is a pre-built ...


Another approach is to create a very fine grid, and use the max-p algorithm. http://pysal.readthedocs.org/en/v1.7/library/region/maxp.html

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