Three-dimensional alpha shapes
ACM Transactions on Graphics (TOG)
Fast computation of generalized Voronoi diagrams using graphics hardware
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
External-Memory Algorithms with Applications in GIS
Algorithmic Foundations of Geographic Information Systems, this book originated from the CISM Advanced School on the Algorithmic Foundations of Geographic Information Systems
Sparse matrix solvers on the GPU: conjugate gradients and multigrid
ACM SIGGRAPH 2003 Papers
Fast and reliable collision detection using graphics processors
SCG '05 Proceedings of the twenty-first annual symposium on Computational geometry
Fast and approximate stream mining of quantiles and frequencies using graphics processors
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
IEEE Micro
ACM SIGGRAPH 2006 Papers
OpenGL(R) Programming Guide: The Official Guide to Learning OpenGL(R), Version 2 (5th Edition) (OpenGL)
TerraStream: from elevation data to watershed hierarchies
Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems
Concurrent number cruncher: a GPU implementation of a general sparse linear solver
International Journal of Parallel, Emergent and Distributed Systems
I/O-efficient construction of constrained delaunay triangulations
ESA'05 Proceedings of the 13th annual European conference on Algorithms
TerraNNI: natural neighbor interpolation on a 3D grid using a GPU
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Accelerating batch processing of spatial raster analysis using GPU
Computers & Geosciences
Constructing natural neighbor interpolation based grid DEM using CUDA
Proceedings of the 3rd International Conference on Computing for Geospatial Research and Applications
Hybrid MPI/GPU interpolation for grid DEM construction
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
GPU-based roofs' solar potential estimation using LiDAR data
Computers & Geosciences
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With modern LiDAR technology the amount of topographic data, in the form of massive point clouds, has increased dramatically. One of the most fundamental GIS tasks is to construct a grid digital elevation model (DEM) from these 3D point clouds. In this paper we present a simple yet very fast algorithm for constructing a grid DEM from massive point clouds using natural neighbor interpolation (NNI). We use a graphics processing unit (GPU) to significantly speed up the computation. To handle the large data sets and to deal with graphics hardware limitations clever blocking schemes are used to partition the point cloud. For example, using standard desktop computers and graphics hardware, we construct a high-resolution grid with 150 million cells from two billion points in less than thirty-seven minutes. This is about one-tenth of the time required for the same computer to perform a standard linear interpolation, which produces a much less smooth surface.