Overview
| DOI | https://doi.org/10.3334/ORNLDAAC/2474 |
|---|---|
| Version | 2 |
| Project | |
| Published |
Description
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.
Science Keywords
- SPECTRAL/ENGINEERING
- LIDAR
- LIDAR WAVEFORM
- BIOSPHERE
- VEGETATION
- CANOPY CHARACTERISTICS
- BIOSPHERE
- VEGETATION
- FOREST COMPOSITION/VEGETATION STRUCTURE
- BIOSPHERE
- ECOSYSTEMS
- TERRESTRIAL ECOSYSTEMS
Data Use and Citation
This dataset is openly shared, without restriction, in accordance with the NASA Earthdata Data Use Guidance.
Data Files
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Companion Files
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Dataset Companion Files
Dataset has 1 companion files.
- GEDI_L4C_WSCI_Fusion.pdf