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Live Fuel Moisture Content (LFMC) is a critical factor in wildfire behavior, and it is used to estimate the ignition probability and spread of fire. This paper shows a methodology for modeling and mapping LFMC in a Mediterranean area of Spain (Cortes de Pallás, Province: Valencia). Field samples were taken biweekly from June 2020 to November 2021 in five plots of shrub areas and in three plots of tree areas. Models were defined by means of stepwise multiple linear regression using Sentinel-2 spectral indices, together with meteorological and topographic data. Spectral indices introduced in models are the Enhanced Vegetation Index (EVI), Moisture Stress Index (MSI), Transformed Chlorophyll Absorption Index (TCARI), Vegetation Index-Green (Vgreen) and Normalized Difference Moisture Index (NDMI). As meteorological variables, we used the accumulated precipitation in the previous 60 days, the average of the mean and minimum temperatures in the previous 15 and 60 days, as well as the average of the minimum relative humidity in the 15 days prior to the date considered. Other topographic variables, such as the terrain slope, were considered as predictors. Moreover, the sine and cosine of the day of the year were also considered to account for the seasonal effect. LFMC predictions for each study plot were obtained considering the weighted average of the FCC (fraction of canopy cover) of each species. In addition, a specific model was defined to obtain LFMC for the Rosmarinus officinalis species in shrub areas. Model predictions were validated using independent field measurements of LFMC, and the results showed a good agreement between the predicted and the measured values. Ultimately, models were extrapolated to obtain results in 2022 for a larger geographic area. Cartographic representation showed spatial and temporal variations in LFMC across the region during the fire seasons of 2021 and 2022.
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