David Riaño Ph.D is an Associate Project Scientist at CSTARS with research interests in environmental applications and remote sensing, focusing on studies of natural hazards (wildfires, floods), agricultural management, the carbon budget and water cycle in the context of climate change.
Title: Evaluation of Fuel Moisture Content Products from MODIS over Europe and Australia Fire ignition and propagation depend on Live Fuel Moisture Content (LFMC). Fuels with high LFMC take longer to ignite and water acts as a heat sink, slowing down fire spread and intensity . LFMC is defined as the water weight of the live fuel over the weight after oven drying it at 60–100 °C for 24–48 h. LFMC Remote Sensing (RS) estimates rely on the spectral response changes caused by the direct impact of liquid water absorption features and the indirect impact of pigment and structural changes associated to water content variations . Two main approaches have been applied, empirical and radiative transfer models (RTM) . RTM only outperform empirical models if they are constrained and structural information is known . LFMC signal needs to be discriminated from atmospheric and topographic effects, sun and sensor geometry, soil background, species composition or other plant characteristics . To compensate for some of these factors, several authors prefer to relate the pixel dynamics to the LFMC dynamics using relative spectral indices normalized for each pixel based on a sufficiently large temporal series . Dr. Marta Yebra (Fenner School of Environment and Society, ANU) developed a MODIS FMC product using RTM inversion techniques . The product is under evaluation in Australia using field data collected in 79 sites spread out in all states (Fig. 1).