Fast exact parallel map overlay using a two-level uniform grid

Abstract

We present EPUG-OVERLAY (Exact Parallel Uniform Grid Overlay), an algorithm to overlay two maps that is fast and parallel, has no roundoff errors, and is freely available. EPUG-OVERLAY combines several novel aspects. It represents coordinates with rational numbers, thereby ensuring exact computations with no roundoff errors and the ensuing sliver problems and topological impossibilities. For efficiency, EPUG-OVERLAY performs the map overlay in parallel, thereby utilizing the ubiquitous multicore architecture. Our application goes beyond merely using existing packages, which are inefficient when used in parallel on large problems. Indeed, overlaying two maps with 53,000,000 edges and 730,000 faces took only 322 elapsed seconds (plus 116 seconds for I/O) on a dual 8-core 3.1 GHz Intel Xeon E5-2687 workstation. In contrast, GRASS, executing sequentially and generating roundoff errors, takes 5300 seconds. The overlay operation combines two input maps (planar graphs) containing faces (polygons) separated by polyline edges (chains), into a new map, each of whose faces is the intersection of one face from each input map. Floating point roundoff errors can cause an edge intersection to be missed or the computed intersection point be in a wrong face, leading to a topological inconsistency. Thus, a program might fail to compute a valid output map at all, using any amount of time. This gets worse when the inputs are bigger or have slivers. Heuristics can ameliorate this problem, but only to an extent. By representing each coordinate as a vulgar fraction, with multiprecision numerator and denominator, the computation is exact. EPUG-OVERLAY also executes various useful subproblems very quickly, such as locating a set of points in a planar graph and finding all the intersections among a large set of small edges. EPUG-OVERLAY is built on our earlier sequential floating-point algorithm that found the areas of the overlay polygons, without finding the polygons themselves.