Assessing GEDI-NASA system for forest fuels classification using machine learning techniques

Assessing GEDI-NASA system for forest fuels classification using machine learning techniques

Identification of forest fuels is a key step for forest fire prevention since they provide valuable information of fire behavior. This study assesses NASA’s Global Ecosystem Dynamics Investigation (GEDI) system to classify fuel types in Mediterranean environments according to the Prometheus model in...

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Bibliographic Details
Main Authors: Raúl Hoffrén, María Teresa Lamelas, Juan de la Riva, Darío Domingo, Antonio Luis Montealegre, Alberto García-Martín, Sergio Revilla
Format: Article
Language:English
Published: Elsevier 2023-02-01
Series:International Journal of Applied Earth Observations and Geoinformation
Subjects:
Full-waveform LiDAR
Landsat-8 OLI
Mediterranean ecosystems
Prometheus
SVM
Random Forest
Online Access:http://www.sciencedirect.com/science/article/pii/S1569843222003636

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http://www.sciencedirect.com/science/article/pii/S1569843222003636

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