Environmental Sciences Proceedings (Dec 2023)

A Linear Regression Model for Live Fuel Moisture Content Estimation during the Fire Season in Shrub Areas of the Province of Valencia in Spain Using Sentinel-2 Remote Sensing Data

  • Kenneth Pachacama-Vallejo,
  • Ángel Balaguer-Beser

DOI
https://doi.org/10.3390/environsciproc2023028012
Journal volume & issue
Vol. 28, no. 1
p. 12

Abstract

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Live Fuel Moisture Content (LFMC) describes the amount of water present in any type of vegetation and helps quantify the amount of fuel available in a wildfire. In this paper, a multivariate linear regression model was built to estimate the LFMC of the weighted average of all shrub-type species present, using the fraction of canopy cover (FCC) of each forest species as weights. Sample training was conducted with field data obtained during the fire season of the years 2019, 2020 and 2021 in 15 plots of a Mediterranean area where vegetation composed of the shrub-type species dominates. Different spectral indices extracted from Sentinel-2 together with the mean surface temperature, the accumulated precipitation and the seasonal parameters were considered as predictors. The results were compared with the extrapolation of another model trained with field data collected in the year 2019.

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