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

本数据集仓库包含570条模拟GEDI (GEDI)波形数据，该批数据于捷克共和国西南部的温带山地森林中采集，采集间隔为51天。所有GEDI波形均由高密度无人机激光雷达数据模拟生成。
- LeafOnSimulatedMetricsAndBiomass.csv：包含冠层叶片完全展开条件下的模拟GEDI RH指标与野外实测地上部生物量密度数据
- LeafOffSimulatedMetricsAndBiomass.csv：包含冠层叶片脱落条件下的模拟GEDI RH指标与野外实测地上部生物量密度数据
- CandidateModels.csv：包含用于预测AGBD的GEDI L4A模型的详细信息
- CushmanEtAl_LeafPhenologyGEDI.R：用于基于GEDI L4A模型预测AGBD、评估系统性预测偏差并生成结果表格与图件的R脚本