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Journal of Applied Remote Sensing

Accuracy assessment of LiDAR-derived digital elevation models in a rural landscape with complex terrain
Author(s): Laura Barreiro-Fernández; Sandra Buján; David Miranda; Ulises Diéguez-Aranda; Eduardo González-Ferreiro
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Paper Abstract

Digital elevation models (DEMs) are essential in many professional areas as they produce georeferenced elevation data that are critical for a wide range of studies, computations, decision-making processes, and derived products. Quality control thus becomes necessary to quantify the accuracy of the information provided. We assessed the accuracy of elevation data estimated by DEMs derived from LiDAR data representing diverse land cover types. For this purpose, we used the FUSION software and explored variations in accuracy in relation to the following factors: input data, interpolation methods, terrain slope, heterogeneity of land cover, and LiDAR point density. We selected and measured 1157 checkpoints by using total station and GPS techniques and following a stratified random design in order to validate the LiDAR-derived DEMs. We used robust estimators, nonparametric tests, and analysis of variance to examine the elevation errors. The study findings showed the following: (1) using the full set of LiDAR returns did not improve elevation accuracy relative to using the last-return data set; (2) using the minimum switch for interpolation did not improve accuracy compared to the default behavior of the interpolator; (3) land cover and slope significantly affected accuracy; (4) DEMs tended to underestimate elevation; and (5) the mean density of the returns classified as ground was significantly affected by land cover and slope factors.

Paper Details

Date Published: 18 February 2016
PDF: 17 pages
J. Appl. Rem. Sens. 10(1) 016014 doi: 10.1117/1.JRS.10.016014
Published in: Journal of Applied Remote Sensing Volume 10, Issue 1
Show Author Affiliations
Laura Barreiro-Fernández, Univ. de Santiago de Compostela (Spain)
Sandra Buján, Univ. de Santiago de Compostela (Spain)
David Miranda, Univ. de Santiago de Compostela (Spain)
Ulises Diéguez-Aranda, Univ. de Santiago de Compostela (Spain)
Eduardo González-Ferreiro, Univ. de Santiago de Compostela (Spain)
Oregon State Univ. (United States)
USDA Forest Service - Pacific Northwest Research Station (United States)

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