Tracking savanna vegetation structure in South Africa by extension of GEDI canopy metrics with Landsat, Sentinel-2, and PALSAR

Adaptive management of savanna ecosystems requires frequent monitoring of woody vegetation structure, and although vegetation structure and changes may be captured with repeat airborne lidar, it is spatially and temporally limited across African savannas. As an alternative, this study evaluates the extension of spaceborne waveform lidar canopy metrics (RH98, Cover, Foliage Height Diversity) from the Global Ecosystem Dynamics Investigation (GEDI) across the Greater Kruger region in South Africa using moderate resolution optical sensors (Landsat and Harmonized Landsat Sentinel-2 [HLS]), L-band Synthetic Aperture Radar (PALSAR-1 and -2), and topographic and soil covariates. We compared the performance of 12 predictor sets incorporating different sensor combinations and temporal processing methods (LandTrendr and CCDC) in random forest models using temporal cross-validation to assess extrapolation accuracy. The most parsimonious fusion model (LandTrendr + SAR + topography/soils) achieved RMSEs of 3.04 m for RH98, 13.38% for Cover and 0.34 for FHD, which was comparable to more complex models using HLS and CCDC. All models demonstrated good temporal transferability with minimal bias but tended to overestimate low values and underestimate high values, which muted the estimated magnitude of change. Annual canopy structure maps derived from the best model captured expected spatial patterns and were used in model-based estimators to quantify changes in areas impacted by elephants, timber harvesting, fuelwood extraction, and woody encroachment. Extending GEDI metrics with moderate-resolution sensors thus offers a viable approach for large-scale savanna monitoring and detecting change in high impact areas. • Spaceborne lidar an alternative to airborne lidar as reference in savanna mapping • GEDI canopy height, cover, and height diversity mapped annually in African savanna • Fusion of LandTrendr processed Landsat with PALSAR yields parsimonious model • Models show good temporal transferability to enable long-term savanna monitoring • Model-based estimators quantify changes from elephants, logging, and encroachment

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Publication Details

Journal
Science of Remote Sensing
Published
2026-02-05
DOI
https://doi.org/10.1016/j.srs.2026.100388
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
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article

Tracking savanna vegetation structure in South Africa by extension of GEDI canopy metrics with Landsat, Sentinel-2, and PALSAR

Patrick A. Fekety, David Bunn, Steven K. Filippelli, Jody C. Vogeler et al.
Science of Remote Sensing
Remote Sensing and LiDAR Applications
article

Tracking savanna vegetation structure in South Africa by extension of GEDI canopy metrics with Landsat, Sentinel-2, and PALSAR

Patrick A. Fekety, David Bunn, Steven K. Filippelli, Jody C. Vogeler, Melissa R. McHale, Corli Coetsee, Francisco Mauro
article en

Abstract

Adaptive management of savanna ecosystems requires frequent monitoring of woody vegetation structure, and although vegetation structure and changes may be captured with repeat airborne lidar, it is spatially and temporally limited across African savannas. As an alternative, this study evaluates the extension of spaceborne waveform lidar canopy metrics (RH98, Cover, Foliage Height Diversity) from the Global Ecosystem Dynamics Investigation (GEDI) across the Greater Kruger region in South Africa using moderate resolution optical sensors (Landsat and Harmonized Landsat Sentinel-2 [HLS]), L-band Synthetic Aperture Radar (PALSAR-1 and -2), and topographic and soil covariates. We compared the performance of 12 predictor sets incorporating different sensor combinations and temporal processing methods (LandTrendr and CCDC) in random forest models using temporal cross-validation to assess extrapolation accuracy. The most parsimonious fusion model (LandTrendr + SAR + topography/soils) achieved RMSEs of 3.04 m for RH98, 13.38% for Cover and 0.34 for FHD, which was comparable to more complex models using HLS and CCDC. All models demonstrated good temporal transferability with minimal bias but tended to overestimate low values and underestimate high values, which muted the estimated magnitude of change. Annual canopy structure maps derived from the best model captured expected spatial patterns and were used in model-based estimators to quantify changes in areas impacted by elephants, timber harvesting, fuelwood extraction, and woody encroachment. Extending GEDI metrics with moderate-resolution sensors thus offers a viable approach for large-scale savanna monitoring and detecting change in high impact areas. • Spaceborne lidar an alternative to airborne lidar as reference in savanna mapping • GEDI canopy height, cover, and height diversity mapped annually in African savanna • Fusion of LandTrendr processed Landsat with PALSAR yields parsimonious model • Models show good temporal transferability to enable long-term savanna monitoring • Model-based estimators quantify changes from elephants, logging, and encroachment

Science of Remote SensingVol. 13
Universidad de Valladolid (ES), South African National Parks (ZA), University of British Columbia (CA), Scientific Services (ZA), Colorado State University (US), Nelson Mandela University (ZA)
Life in Land
Openalex Percentile: Top 69%
Remote Sensing and LiDAR Applications
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