This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1029/2022EA002516. This is version 1 of this Preprint.
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Abstract
The Global Ecosystem Dynamics Investigation (GEDI) lidar is a multibeam laser altimeter on the International Space Station (ISS). GEDI is the first spaceborne instrument designed to measure vegetation height and to quantify aboveground carbon stocks in temperate and tropical forests and woodlands. This document describes the algorithm theoretical basis underpinning the development of the GEDI Level-4A (GEDI04_A) footprint aboveground biomass density (AGBD) data product. The GEDI04_A data product contains estimates of AGBD for individual GEDI footprints and associated prediction intervals. The algorithm uses GEDI02_A relative height (RH) metrics and 13 linear models to predict AGBD in 32 combinations of plant functional type (PFT) and world region within the observation limits of the ISS. GEDI04_A models for the release 1 and release 2 data products were developed using 8,587 quality-filtered simulated GEDI waveforms associated with field estimates of AGBD in 21 countries. Although this is the most geographically comprehensive data available for the development of AGBD models using lidar remote sensing, important regions are underrepresented, including the forests of continental Asia, deciduous broadleaf forests and savannas of the dry tropics, and evergreen broadleaf forests north of Australia. We describe the scientific and mathematical assumptions required to develop globally representative estimates of AGBD using GEDI lidar, including generalization beyond training data, and exclusion of GEDI02_A observations that do not meet requirements of the GEDI04_A algorithm. The footprint-level predictions generated by this process provide globally comprehensive estimates of AGBD. These footprint-level predictions are a prerequisite for the GEDI GEDI04_B gridded AGBD data product.
DOI
https://doi.org/10.31223/X5V93D
Subjects
Engineering, Physical Sciences and Mathematics
Keywords
Carbon cycle, ecosystem structure, Global Ecosystem Dynamics Investigation, lidar, Remote Sensing
Dates
Published: 2022-08-14 01:31
Last Updated: 2022-08-14 08:31
License
CC BY Attribution 4.0 International
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Conflict of interest statement:
None
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