Parallel Computing Flow Accumulation in Large Digital Elevation Models
نویسندگان
چکیده
منابع مشابه
Parallel Computing Flow Accumulation in Large Digital Elevation Models
This paper describes a new fast and scalable parallel algorithm to compute global flow accumulation for automatic drainage network extraction in large digital elevation models (DEM for short). Our method uses the D8 model to compute the flow directions for all pixels in the DEM (except NODATA and oceans). A parallel spanning tree algorithm is proposed to compute hierarchical catchment basins to...
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This paper presents a fast and flexible parallel implementation to compute catchment basins in the large digital elevation models (DEM for short). This algorithm aims at using all the specific properties of the problem to optimize local computations and to avoid useless communications or synchronizations. The algorithm has been implemented in MPI and the first benchmarks show the scalability of...
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Continent-scale datasets challenge hydrological algorithms for processing digital elevation models. Flow accumulation is an important input for many such algorithms; here, I parallelize its calculation. The new algorithm works on one or many cores, or multiple machines, and can take advantage of large memories or cope with small ones. Unlike previous algorithms, the new algorithm guarantees a f...
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This paper introduces a set of parallel algorithms to determine the hydrological flow direction and contributing area of each cell in a digital elevation model (DEM) using cluster computers in an MPI programming model. DEMs are partitioned across processes relevant to the physical layout of the terrain such that processes with adjacent ranks calculate flow direction and contributing areas for p...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2011
ISSN: 1877-0509
DOI: 10.1016/j.procs.2011.04.248