GEDI L4C Global Waveform Structural Complexity Index (WSCI) Fusion Product, Version 2

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Authors: Tiago de Conto, John David Armston, Ralph Dubayah
Cited by: 0

Abstract

This dataset provides global, wall-to-wall estimates of the Waveform Structural Complexity Index (WSCI) at 25-meter spatial resolution with 3-monthly temporal frequency from 2015 to 2022. The product advances the sparse footprint-level GEDI L4C product by using deep learning to fuse spaceborne lidar observations with multi-sensor Synthetic Aperture Radar (SAR) data, producing spatially continuous estimates of forest structural complexity. The dataset employed an adapted EfficientNet version 2 architecture that integrates Sentinel-1 C-band, ALOS-2 PALSAR-2 L-band SAR mosaics, and Copernicus Digital Elevation Model data. Each 25-meter pixel contains the mean WSCI estimate along with quantified uncertainties (aleatoric and epistemic standard deviations) and data quality indicators. Model training utilized approximately 133 million GEDI footprints collected within the operational domain (51.6 degrees N to 51.6 degrees S) from April 2019 to December 2022, with predictions extending both temporally (2015-2022) and spatially (beyond GEDI's latitude limits) through the fusion approach.

Fields of Study & Subjects

Remote Sensing and LiDAR Applications Synthetic Aperture Radar (SAR) Applications and Techniques Remote Sensing in Agriculture

Publication details

Journal / source
Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics
Publication date
3 February 2026
Language
EN