Cited by 483

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Accuracy of Airborne Lidar-Derived Elevation

Hodgson, Michael E., Bresnahan, Patrick·2004·Photogrammetric Engineering & Remote Sensing

Abstract

As part of a countywide large-scale mapping effort for Richland County, South Carolina, an accuracy assessment of a recently acquired lidar-derived data set was conducted. Airborne lidar (2-m nominal posting) was collected at a flying height of 1207 meters above ground level (AGL) using an Optech ALTM (Airborne Laser Terrain Mapper) 1210 system. Unique to this study are the reference point elevations. Rather than using an interpolation approach for gathering observed elevations at reference points, the x-y coordinates of lidar points were located in the field and these elevations were surveyed. Using both total-station-based and rapid-static GPS techniques, observed vertical heights were measured at each reference lidar posting. The variability of vertical accuracy was evaluated for six land-cover categories. Root-meansquared error (RMSE) values ranged from a low of 17 to 19 cm (pavement, low grass, and evergreen forests) to a high of 26 cm (deciduous forests). The unique error assessment of lidar postings also allowed for the creation of an error budget model. The observed lidar elevation error was decomposed into errors from lidar system measurements, horizontal displacement, interpolation error, and surveyor error. A crossvalidation approach was used to assess the observed interpolated lidar elevation error for each field-verified reference point. In order of decreasing importance, the lidar system measurements were the dominant source of error followed by interpolation er…

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Crossref · 10.14358/pers.70.3.331

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  • Errors in the DEM can be reduced through high-resolution, high-accuracy DEMs such as lidar, but cannot be fully eliminated.

    “Whilst errors in the DEM can be reduced through the use of high-resolution, highaccuracy DEMs derived from sources such as lidar (light detection and ranging), error cannot be fully eliminated (Aguilar et al., 2010;Hodgson & Bresnahan, 2004).”

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Research works printed but not linked: 10

  1. J.C. Adams, 2002, Evaluation of lidar and medium scale photogrammetry for detecting soft-cliff coastal change, Photogrammetric Record, 17, 405, 10.1111/0031-868X.00195 · DOI
  2. Z.H. Bowen, 2002, Evaluation of light detection and ranging (lidar) for measuring river corridor topography, Journal of the American Water Resources Association, 38, 33, 10.1111/j.1752-1688.2002.tb01532.x · DOI
  3. D.M. Cobby, 2001, Image processing of airborne laser altimetry data for improved river modeling, ISPRS Journal of Photogrammetry and Remote Sensing, 56, 121, 10.1016/S0924-2716(01)00039-9 · DOI
  4. D.J. Cowen, 2000, A GIS-assisted rail construction econometric model that incorporates lidar data, Photogrammetric Engineering & Remote Sensing, 66, 1323
  5. I. Dowman, 2001, A comparison of airborne IfSAR and LIDAR data over the Vaihingen test site, 160
  6. M.E. Hodgson, 2003, An evaluation of lidar- and IFSAR-derived digital elevation models in leaf-on conditions with USGS Level 1 and Level 2 DEMs, Remote Sensing of Environment, 84, 295, 10.1016/S0034-4257(02)00114-1 · DOI
  7. C.D. Lloyd, 2002, Deriving DSMs from lidar data with kriging, International Journal of Remote Sensing, 23, 2519, 10.1080/01431160110097998 · DOI
  8. A.M. MacEachren, 1987, Sampling and isometric mapping of continuous geographic surfaces, The American Cartographer, 14, 299, 10.1559/152304087783875723 · DOI
  9. D.H. Maling, 1989, Measurements from Maps, 577
  10. G.T. Raber, 2002, Creation of digital terrain models using an adaptive lidar vegetation point removal process, Photogrammetric Engineering & Remote Sensing, 68, 1307

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Metadata

Authors
Hodgson, M. E., & Bresnahan, P.
Venue
Photogrammetric Engineering & Remote Sensing
Published
2004-03-01
Volume
70
Issue
3
Pages
331-339
ISSN
0099-1112
Cited by
483
References
0
Language
en

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