Evaluating the performance of spectral indices and meteorological variables as indicators of live fuel moisture content in Mediterranean shrublands

Evaluating the performance of spectral indices and meteorological variables as indicators of live fuel moisture content in Mediterranean shrublands

This article presents a methodology to estimate the live fuel moisture content (LFMC), a critical factor in the spread of forest fires, through machine learning tools. Random forest models were trained using field LFMC samples collected bi-weekly for 18 consecutive months in 43 shrubland plots in th...

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Bibliographic Details
Main Authors: María Alicia Arcos, Ángel Balaguer-Beser, Luis Ángel Ruiz
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Ecological Indicators
Subjects:
Sentinel-2
Spectral indices
Forest fire
Meteorological data
Climate change
Machine Learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1470160X24013517
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