Point Cloud and DEM-Based Lidar Differencing Products from Hickory Nut Gorge, NC

This dataset contains lidar differencing products developed to support the Earth Surface Processes and Landforms manuscript: “A Storm Sculpted Landscape – observations from post-Helene lidar in the Hickory Nut Gorge, North Carolina” by Scheip, Lang, et al. This repository supports transparency during peer review and reproducibility following publication. It may be updated upon acceptance of the manuscript. The files included are: lidar-diff-pc-2017-v-2020.tif lidar-diff-pc-2017-v-2024.tif lidar-diff-pc-2020-v-2024.tif lidar-diff-2020-minus-2024.tif The lidar-diff-pc files represent 3D surface change between lidar point cloud acquisitions using the Iterative Closest Point (ICP) alignment and Multiscale Model to Model Cloud Comparison (M3C2) algorithm, implemented in a commercial GPU-accelerated workflow by Cambio Earth (Weidner et al., 2023; https://www.cambioearth.com). This method allows for high-precision surface change detection normal to terrain, particularly effective in steep, vegetated landscapes. Full parameter details and filtering procedures are provided in the manuscript Supplement. The lidar-diff-2020-minus-2024.tif file was created by subtracting the 2024 1 m DEM from the 2020 1 m DEM and applying a vertical offset correction (detrending) to account for systematic bias between the datasets. This raster corrects for mean vertical alignment differences between DEMs. License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) These data may be reused for academic, non-commercial purposes with appropriate citation. See license details for more information. Citation (suggested): Scheip, C., Lang, K., Wegmann, K. (2025). Lidar differencing products supporting “A Storm Sculpted Landscape – observations from post-Helene lidar in the Hickory Nut Gorge, North Carolina” [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.15600354 Reference: Weidner, L., Ferrier, A., van Veen, M., & Lato, M. J. (2023). Rapid 3D lidar change detection for geohazard identification using GPU-based alignment and M3C2 algorithms. Canadian Geotechnical Journal, 61(5), 896-914.