60620 20210301081639.0 doi 10.3390/rs70708631 sideral 91589 ART-2015-91589 eng (orcid)0000-0001-6288-2780 Montealegre, A.L. Universidad de Zaragoza Interpolation routines assessment in ALS-derived Digital Elevation Models for forestry applications 2015 Access copy available to the general public Unrestricted Airborne Laser Scanning (ALS) is capable of estimating a variety of forest parameters using different metrics extracted from the normalized heights of the point cloud using a Digital Elevation Model (DEM). In this study, six interpolation routines were tested over a range of land cover and terrain roughness in order to generate a collection of DEMs with spatial resolution of 1 and 2 m. The accuracy of the DEMs was assessed twice, first using a test sample extracted from the ALS point cloud, second using a set of 55 ground control points collected with a high precision Global Positioning System (GPS). The effects of terrain slope, land cover, ground point density and pulse penetration on the interpolation error were examined stratifying the study area with these variables. In addition, a Classification and Regression Tree (CART) analysis allowed the development of a prediction uncertainty map to identify in which areas DEMs and Airborne Light Detection and Ranging (LiDAR) derived products may be of low quality. The Triangulated Irregular Network (TIN) to raster interpolation method produced the best result in the validation process with the training data set while the Inverse Distance Weighted (IDW) routine was the best in the validation with GPS (RMSE of 2.68 cm and RMSE of 37.10 cm, respectively). info:eu-repo/grantAgreement/ES/UZ/CUD2014-HUM-01 info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.036 2015 REMOTE SENSING 5 / 28 = 0.179 2015 Q1 T1 1.349 2015 Earth and Planetary Sciences (miscellaneous) 2015 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion (orcid)0000-0002-8954-7517 Lamelas, M.T. (orcid)0000-0003-2615-270X De La Riva, J.R. Universidad de Zaragoza 3006 010 Universidad de Zaragoza Dpto. Geograf. Ordenac.Territ. Área Análisis Geográfico Regi. 7, 7 (2015), 8631-8654 Remote sens. (Basel) Remote Sensing 2072-4292 4546246 http://zaguan.unizar.es/record/60620/files/texto_completo.pdf Versión publicada 89579 http://zaguan.unizar.es/record/60620/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:60620 articulos driver 2021-03-01-08:01:24 ARTICLE