Constraining plant functional types in a semi-arid ecosystem with waveform lidar

Accurate classification of plant functional types (PFTs) reduces the uncertainty in global biomass and carbon estimates. Airborne small-footprint waveform lidar data are increasingly used for vegetation classification and above-ground carbon estimates at a range of spatial scales in woody or homogen...

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Veröffentlicht in:	Remote sensing of environment 2018-05, Vol.209, p.497-509
Hauptverfasser:	Ilangakoon, Nayani T., Glenn, Nancy F., Dashti, Hamid, Painter, Thomas H., Mikesell, T. Dylan, Spaete, Lucas P., Mitchell, Jessica J., Shannon, Kyle
Format:	Artikel
Sprache:	eng
Schlagworte:	Airborne observation Airborne Snow Observatory Aridity Artificial intelligence Backscatter Backscattering Carbon Classification Drylands Ecosystems Ensemble Environment models Environmental impact Feature selection Lidar Machine learning Plant functional types Pulse duration Random forest Shrubs Spatial discrimination Spatial resolution Time dependence Uncertainty Vegetation Watersheds Waveform analysis Waveform lidar
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