Test DTM for "Caldera Blanca" (Lanzarote Island), used in the submitted paper on surface roughness analysis in geomorphometry

The uploaded DTM “Lanzarote.tif” is used as testing surface for the following paper: Trevisani, S., & Guth, P. L. (2025). Surface Roughness in Geomorphometry: From Basic Metrics Toward a Coherent Framework. Remote Sensing, 17(23), 3864. https://doi.org/10.3390/rs17233864 The DTM has been derived by means of interpolation of lidar point cloud available at: https://centrodedescargas.cnig.es/CentroDescargas/lidar-tercera-cobertura. At the cited portal you will find the tiles of the LiDAR 3D point clouds with national coverage and colored with 4 bands (RGBI), corresponding to the third topographic lidar survey for Spain (2022-2025). From the same lidar point cloud RGB imagery has been derived at 1 m resolution ("lanzaroteRGB.tif"). The shapefiles included represent areas considered in the submitted paper to perform the analysis and design figures. The statistical correlations between different surface roughness indices have been computed for the spatial domain represented by "AOIbasics.shp". Some characteristics of the lidar point cloud tiles derived from the web portal: GRS: ETRS89 in the mainland Spain, Balearic Islands, Ceuta and Melilla, and REGCAN95 in the Canary Islands (both systems compatible with WGS84). UTM projection in the corresponding zone. Orthometric heights. Format: LAZ (LAS compression file format) file. Average point density: 5 points/m² or greater The 2 m DTM has been derived interpolating the ground points using the function "LAS data set to raster" of ArcGIS Pro Esri (version 3.4.0); parameters used: binning, average and void filling via natural neighbor interpolation. Given that the point clouds have been downloaded from the website of the General Directorate of the National Geographic Institute of Spain and are covered by CC-BY 4.0 license, the derived digital terrain model and RGB imagery are a “Obra derivada de LiDAR-PNOA-cob3 2022-2025 CC-BY 4.0 scne.es” Below for your convenience some of the R key commands (commented) used for the paper with this dataset