Mapping global forest canopy height through integration of GEDI and Landsat data

Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard...

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Bibliographic Details
Published in:Remote sensing of environment 2021-02, Vol.253, p.112165, Article 112165
Main Authors: Potapov, Peter, Li, Xinyuan, Hernandez-Serna, Andres, Tyukavina, Alexandra, Hansen, Matthew C., Kommareddy, Anil, Pickens, Amy, Turubanova, Svetlana, Tang, Hao, Silva, Carlos Edibaldo, Armston, John, Dubayah, Ralph, Blair, J. Bryan, Hofton, Michelle
Format: Article
Language:English
Subjects:
Canopies
Carbon emissions
Ecosystem dynamics
Emissions
Forest canopy
Forest degradation
Forest ecosystems
Forest height
Forest monitoring
Forests
GEDI
Global climate
Imagery
Integration
International Space Station
Landsat
Landsat satellites
Lidar
Monitoring
Remote sensing
Space stations
Spatial discrimination
Spatial resolution
Sustainable development
Time-series
Vegetation
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Summary:Consistent, large-scale operational monitoring of forest height is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. The Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019. Here, we employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements, creating a 30 m spatial resolution global forest canopy height map for the year 2019. The global forest height map was compared to the GEDI validation data (RMSE = 6.6 m; MAE = 4.45 m, R2 = 0.62) and available airborne lidar data (RMSE = 9.07 m; MAE = 6.36 m, R2 = 0.61). The demonstrated integration of GEDI data with time-series optical imagery is expected to enable multidecadal historic analysis and operational forward monitoring of forest height and its dynamics. Such capability is important to support global climate and sustainable development initiatives.
ISSN:0034-4257
1879-0704
DOI:10.1016/j.rse.2020.112165