Facilitates efficient polygon search using kd trees. Coordinate level spatial data can be aggregated to higher geographical identities like census blocks, ZIP codes or police district boundaries. This process requires mapping each point in the given data set to a particular identity of the desired geographical hierarchy. Unless efficient data structures are used, this can be a daunting task. The operation point.in.polygon() from the package sp is computationally expensive. Here, we exploit kd-trees as efficient nearest neighbor search algorithm to dramatically reduce the effective number of polygons being searched.
|Author||Markus Loecher <firstname.lastname@example.org> and Madhav Kumar <email@example.com>|
|Date of publication||2014-01-28 16:28:53|
|Maintainer||Markus Loecher <firstname.lastname@example.org>|
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