Multi-temporal airborne lidar data from the Paint Rock Forest Dynamics Plot (2024-2026)
Description
This repository contains data and code underlying the manuscript "Assessing the use of multitemporal, disparate lidar datasets for characterizing aboveground biomass and mortality in a mature Appalachian forest".
Multitemporal lidar offers a potentially powerful tool for detecting forest mortality across broad spatial scales. Multitemporal lidar data are also increasingly available through low-cost drone platforms and efforts like the United States Geological Survey 3D Elevation Program (3DEP). However, these datasets may not always meet established “best practices” for estimating biomass with airborne lidar, including adequate penetration to measure ground elevation and data collection during peak growing season.
This dataset contains drone lidar data collected over the 20-hectare Paint Rock Forest Dynamics Plot (PRFDP) in Northeastern Alabama, in addition to quadrat-level summaries of aboveground biomass and change/mortality from the first and second censuses of the PRFDP. The data accompany an analysis that evaluates the applicability of low-cost drone lidar and 3DEP lidar for quantifying standing biomass and characterizing biomass change. For reproducibility of that manuscript, we also include airborne lidar data from the Paint Rock Forest Dynamics plot available through the USGS 3DEP program during the first census of the PRFDP.
Specifically, we explore using available 3DEP elevation data to overcome limited ground information in low-cost drone lidar, and we explore processing options for making canopy height models from leaf-off 3DEP data more comparable to leaf-on data. We also explore the effect of quadrat size (0.04 or 0.25 ha) and plot biomass estimation method (stem-localized or crown-distributed) on correspondence between plot- and lidar-derived metrics.
This dataset includes original lidar point clouds and the digital elevation model provided by 3DEP, derived products (canopy height models) and associated R code to create them from lidar data, and R code to conduct analyses related derived products and aboveground biomass/change.
We also include raw data and point clouds for other drone lidar collection dates (leaf-off and leaf-on data from 2025, and leaf-on data from 2026) over the Paint Rock Forest Dynamics Plot that were not analyzed in the associated manuscript. These datasets are provided in case they are of use for future studies. Level 2 and 3 products (e.g. canopy height models, aboveground biomass density estimates) are not provided for these other dates, but provided code could be adapted to produce them.
Funding Information
DOE Contract Number
AC05-00OR22725Originating Research Organization
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)Other Contributing Organizations
Department of Natural Resources and Environmental Sciences, Alabama A & M University; Department of Geographical Sciences, University of Maryland, College Park; The Nature Conservancy Sharp Bingham Mountain Preserve; Paint Rock Forest Research CenterSponsoring Organization
Office of Science (SC); Laboratory Directed Research and Development (LDRD) ProgramDetails
Release Date
September 25, 2026Subject
ENVIRONMENTAL SCIENCESKeywords
LidarDataset
Dataset Type
SM Specialized MixSoftware
R; CloudCompareOther Contract Number(s)
USDA NIFA Evans-Allen #1024525 and Capacity Building Grant #006531; US National Science Foundation #1920908; The Lyndhurst FoundationCite This Dataset:
Cushman, K., Czech, H., Grubinger, S., Knight, P., Krassovski, M., Tenorio, E., Lemke, D. (2026). Multi-temporal airborne lidar data from the Paint Rock Forest Dynamics Plot (2024-2026). Oak Ridge National Laboratory. https://doi.org/10.13139/ORNLNCCS/3362725.
Acknowledgements
This work was carried out [in part] at Oak Ridge National Laboratory, managed by UT-Battelle, LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725.