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TerraNNI: Natural Neighbor Interpolation on 2D and 3D Grids Using a GPU

Published: 21 June 2016 Publication History

Abstract

With modern focus on remote sensing technology, such as LiDAR, the amount of spatial data, in the form of massive point clouds, has increased dramatically. Furthermore, repeated surveys of the same areas are becoming more common. This trend will only increase as topographic changes prompt surveys over already scanned areas, in which case we obtain large spatiotemporal datasets.
An initial step in the analysis of such spatial data is to create a digital elevation model representing the terrain, possibly over time. In the case of spatial (spatiotemporal, respectively) datasets, these models often represent elevation on a 2D (3D, respectively) grid. This involves interpolating the elevation of LiDAR points on these grid points.
In this article, we show how to efficiently perform natural neighbor interpolation over a 2D and 3D grid. Using a graphics processing unit (GPU), we describe different algorithms to attain speed and GPU-memory tradeoffs. Our experimental results demonstrate that our algorithms not only are significantly faster than earlier ones but also scale to much bigger datasets that previous algorithms were unable to handle.

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Cited By

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  • (2023)Terrain trees: a framework for representing, analyzing and visualizing triangulated terrainsGeoinformatica10.1007/s10707-022-00472-327:3(525-564)Online publication date: 1-Jul-2023
  • (2021)Application of Gaussian Radial Basis Functions for Fast Spatial Imaging of Ground Penetration Radar Data Obtained on an Irregular GridElectronics10.3390/electronics1023296510:23(2965)Online publication date: 28-Nov-2021
  • (2020)Adaptive Switching Interpolation Filter for Restoring Impulse Corrupted Digital ImagesIET Image Processing10.1049/iet-ipr.2019.1445Online publication date: 14-May-2020

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      Published In

      cover image ACM Transactions on Spatial Algorithms and Systems
      ACM Transactions on Spatial Algorithms and Systems  Volume 2, Issue 2
      Invited Papers from ACM SIGSPATIAL
      July 2016
      107 pages
      ISSN:2374-0353
      EISSN:2374-0361
      DOI:10.1145/2960926
      • Editor:
      • Hanan Samet
      Issue’s Table of Contents
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 21 June 2016
      Accepted: 01 May 2015
      Revised: 01 March 2015
      Received: 01 August 2014
      Published in TSAS Volume 2, Issue 2

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      Author Tags

      1. GIS
      2. GPU
      3. LIDAR
      4. massive data
      5. natural neighbor interpolation

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      Cited By

      View all
      • (2023)Terrain trees: a framework for representing, analyzing and visualizing triangulated terrainsGeoinformatica10.1007/s10707-022-00472-327:3(525-564)Online publication date: 1-Jul-2023
      • (2021)Application of Gaussian Radial Basis Functions for Fast Spatial Imaging of Ground Penetration Radar Data Obtained on an Irregular GridElectronics10.3390/electronics1023296510:23(2965)Online publication date: 28-Nov-2021
      • (2020)Adaptive Switching Interpolation Filter for Restoring Impulse Corrupted Digital ImagesIET Image Processing10.1049/iet-ipr.2019.1445Online publication date: 14-May-2020

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