Abstract
ABSTRACTFuel moisture content (FMC) is a critical parameter in fire behavior prediction. Although remote sensing is an efficient way to estimate the spatial and temporal variations of FMC, most of the existing spectral indices are oriented to live fuels. Estimation of dead fuels is commonly done using weather indices instead. In this study, dehydration experiments were designed for both live and dead fallen litter leaves in order to determine the best hyperspectral indices for different fuel types by tracking the time-varying water contents of both fuel materials. The identified best index for FMC including both fuel types was a derivative spectra-based normalized index (dND) of dND(1900, 2095) with an R2 of 0.85 and an RMSE of 32%. Estimation of FMC in both fuel types were well separated by normalizing dND(1900, 2095) combined with NDVI ((dND-NDVI)/(dND+NDVI)). In addition, new indices were also identified for practical large scale applications when atmospheric water vapor absorption must be taken into account. All the recommend indices should be validated with more plant species in the future.
Highlights
Fuel moisture content (FMC) has an overwhelming importance in understanding different eco-physiological processes and wildfire behavior prediction among all the forest fuel properties as it significantly affects wildfire ignition and propagation and CO2 emission from the combustion of organic materials [Rothermel, 1972; Viegas et al, 1992; Chuvieco et al, 2004a; van der Werf et al, 2004; Yebra et al, 2008; Yebra et al, 2013]
Those indices are usually designed based on the absorption features of leaf water or leaf dry matter only but having ignored the fact that FMC is regulated by both parameters, several indices were found to be correlated with FMC (Table 2)
Four commonly used types of indices (R, D, SR, ND) and two treatments of reflectance were used to estimate FMC for both green and litter fuels based on leaf dehydration experiments. derivative spectra-based normalized index (dND)(1900, 2095) was identified as the best index to estimate FMC, which performed much better than previously reported indices
Summary
Fuel moisture content (FMC) has an overwhelming importance in understanding different eco-physiological processes and wildfire behavior prediction among all the forest fuel properties as it significantly affects wildfire ignition and propagation and CO2 emission from the combustion of organic materials [Rothermel, 1972; Viegas et al, 1992; Chuvieco et al, 2004a; van der Werf et al, 2004; Yebra et al, 2008; Yebra et al, 2013]. FMC can be categorized into two different components based on fuel type: the water content in dead fuels, which are most to ignite (e.g. dry leaves, litter and fallen branches), and that in live fuels (e.g. live leaves). Direct measurements of FMC are severely limited by the available reliable data obtained from field sampling, for large areas where such sampling is generally not feasible.
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