Global fuel moisture content mapping from MODIS
نویسندگان
چکیده
Fuel moisture content (FMC) of live vegetation is a crucial wildfire risk and spread rate driver. This study presents the first daily FMC product at global scale 500 m pixel resolution from Moderate Resolution Imaging Spectroradiometer (MODIS) radiative transfer models (RTMs) inversion techniques. Firstly, multi-source information parameterized PROSPECT-5 (leaf level), 4SAIL (grass shrub canopy level) GeoSail (tree RTMs to generate three look-up tables (LUTs). Each LUT contained most realistic model inputs range combination, corresponding simulated spectra. Secondly, for each date location interest, landcover map classified fuels into classes: grassland, shrubland forest. For fuel class, best LUT-based strategy based on spectral information, cost function, percentage solutions, central tendency determined optimal product. Finally, 3,034 measurements 120 worldwide sites validated statistically significant results (R2 = 0.62, RMSE 34.57%, p < 0.01). Filtering out low quality field achieved better accuracy 0.71, 32.36%, 0.01, n 2008). It anticipated that this can assist in danger modeling, early prediction, suppression response, as well improve awareness life property.
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ژورنال
عنوان ژورنال: International journal of applied earth observation and geoinformation
سال: 2021
ISSN: ['1872-826X', '1569-8432']
DOI: https://doi.org/10.1016/j.jag.2021.102354