Forest Structural Diversity of Central Africa and the Western US mapped using GEDI

Overview

Description

This dataset holds maps of forest structure and structural diversity metrics at a range of spatial scales (1, 5, 10, 15, 20 and 25 km) derived from NASA's Global Ecosystem Dynamics Investigation (GEDI) spaceborne lidar data collected between April 2019 and March 2023. It also holds the airborne laser scanning (ALS) data that provides simulated GEDI waveforms and was used to evaluate the GEDI-derived metrics. Forest structural diversity is a key component of ecosystem diversity and essential for informing conservation and restoration strategies in the face of rapid global climate change and biodiversity loss. Structural metrics include canopy height at 25th and 98th percentiles, plant area index, canopy cover, and foliage height diversity. Structural diversity metrics include richness, evenness, and divergence. Focusing on two biodiversity global hotspots in Central Africa and the western US, GEDI-derived forest structural metrics were validated at 1 km2 resolution over 391 km2 of airborne ALS coverage. GEDI-derived metrics showed robust correlations with ALS data, particularly in dense, flat Central African forests (R2 up to 0.85) compared to more variable terrains like the California Sierra Nevada (R2 up to 0.55). Structural diversity was calculated through probability density-based methods that consider multivariate forest structural metrics. GEDI canopy height (rh98), canopy cover, and foliage height diversity were effective metrics for capturing structural diversity with an R2 of 0.37 when compared to wall-to-wall ALS data at 1-km2 scale. The maps reveal high structural diversity in mid elevation and coastal forests in the western U.S. and in Central African forest-savanna transitions and volcanic ranges, aligning with ecological processes related to disturbance, wildfires and topographic gradients and aridity. The data are provided in GeoTIFF and comma separated values (CSV) formats. A map of the western US study area is provided in a Keyhole Markup Language (KML) file.

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