3D_mapping_data.zip

Data to support the paper:D'Urban Jackson, T., Williams, G.J., Walker-Springett, G. and Davies, A.J., 2020. Three-dimensional digital mapping of ecosystems: a new era in spatial ecology. <i>Proceedings of the Royal Society B</i>, <i>287</i>(1920), p.20192383.<br><br>Point cloud data collected using terrestrial laser scanning and structure-from-motion photogrammetry of three habitats at three scales. The pointcloud folders contain these data which have been processed, aligned, cleaned and subsampled to similar densities for analysis. The datasets for each habitat and scale combination were compared to test the accuracy of structure-from-motion models in different scenarios using the terrestrial laser scanning data as a baseline, and to explore differences in the data characteristics. The point-by-point distance between pointclouds was calculated using the multiscale model to model cloud comparison algorithm (M3C2) implemented in the open source software CloudCompare. The resulting distances and other local statistics are contained as attributes in a single point cloud for each habitat-scale combination, subsampled randomly to 100,000 points (M3C2 folders). The R script summarises the point-by-point distances between point clouds as mean absolute error (MAE) and standard deviation.