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Streaming processing of spatial data Terrain Modeling Visualization Group: Jack Snoeyink, Shawn Brown, Catalin Constantin, David Millman, Georgi Tsankov, Vishal Verma Waldo Tobler’s 1 st Law of Geography: “Everything is related to everything else, but near things are more related than distant things.” Motivation Streaming Mesh Streaming points begin by transmitting a grid or quad-tree with the number of points contained in each cell, allowing for finalization. Streaming Points A streaming mesh specifies interleaved vertices and triangles, in addition vertices not used by subsequent triangles are finalized. After Hurricane Floyd, North Carolina used LIDAR to acquire elevation data for the entire state. Billions of sample points were to be processed into raster elevation maps by Delaunay triangulation. Existing external memory methods are slow and require temp. storage for GB of auxiliary data structures. Using streaming we process 6 million points into a terrain model on an “average” laptop Example Processing Pipeline Experimental Results v 1.32 0.12 0.23 v 1.43 0.23 0.92 v 0.91 0.15 0.62 f 1 2 3 done 2 v 0.72 0.34 0.35 f 4 1 3 done 1 vertices finalized not used by subsequent triangles vertices introduced not used by preceding triangles active

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  • Streaming processing of spatial data

    Terrain Modeling Visualization Group: Jack Snoeyink, Shawn Brown, Catalin Constantin, David Millman, Georgi Tsankov, Vishal Verma

    Waldo Tobler’s 1st Law of Geography: “Everything is related to everything else, but near things are more related than distant things.”

    Motivation

    Streaming Mesh

    Streaming points begin by transmitting a grid or quad-tree with the number of points contained in each cell, allowing for finalization.

    Streaming Points

    A streaming mesh specifies interleaved vertices and triangles, in addition vertices not used by subsequent triangles are finalized.

    After Hurricane Floyd, North Carolina used LIDAR to acquire elevation data for the entire state. Billions of sample points were to be processed into raster elevation maps by Delaunay triangulation. Existing external memory methods are slow and require temp. storage for GB of auxiliary data structures.

    Using streaming we process 6 million points into a terrain model on an “average” laptop

    Example Processing Pipeline Experimental Results

    v 1.32 0.12 0.23 v 1.43 0.23 0.92 v 0.91 0.15 0.62 f 1 2 3 done 2 v 0.72 0.34 0.35 f 4 1 3 done 1 ⋮ ⋮ ⋮ ⋮

    vertices finalized

    not used by subsequent

    triangles

    vertices introduced

    not used by preceding triangles

    active