Data for "Impact of leaf phenology on estimates of aboveground biomass density in a deciduous broadleaf forest from simulated Global Ecosystem Dynamics Investigation (GEDI) lidar."

This repository contains data from 570 simulated GEDI waveforms collected 51 days apart in a temperate mountain forest in the southwest Czech Republic. GEDI waveforms were simulated from high-density drone lidar data. - LeafOnSimulatedMetricsAndBiomass.csv: simulated GEDI RH metrics from leaf-on conditions and field-estimated aboveground biomass density - LeafOffSimulatedMetricsAndBiomass.csv: simulated GEDI RH metrics from leaf-off conditions and field-estimated aboveground biomass density - CandidateModels.csv: details of GEDI L4A models used to predict AGBD - CushmanEtAl_LeafPhenologyGEDI.R: R script to predict AGBD from GEDI L4A models, assess systematic prediction differences, and create results tables and figures