Applying remote sensing information to build fuel load and fuel moisture maps over Portugal

Abstract

Portugal will be warmer and drier under future scenario projections linked to climate change, favouring more extreme wildfire events. As we know, fire has a worldwide scale with a critical role in water and carbon cycles. For this reason, it is essential to know and understand the vegetation dynamic and its role in the Earth system. Remote sensing can be helpful for better comprehension, once it is able to cover large areas with good temporal consistency. In such a context, within the framework of the PyroC.pt project, we intend to improve the representation of fuel load and moisture content from satellite data for use in fire propagation numerical modelling. In this work, three above-ground biomass (AGB) datasets were used: first, samples collected by “Instituto da Conservação da Natureza e das Florestas” (ICNF) in 2015 for the Portuguese National Forest Inventory; second, AGB derived from ~3.000 trees in-situ dendrometric variables measurements (total height, tree diameter at 1.30m above the ground) collected in the Herdade da Mitra at the University of Evora for 2020 and 2021; and third, AGB derived from eucalyptus trees on a field site in Serra de Ossa between 2016 and 2021 provided by the Navigator company. To predict the AGB, these samples combined with satellite data information were used to build a model with more than 20 variables (spectral bands and vegetation indexes). Preliminary results show good agreement between reference and predicted values. Otherwise, we are collecting biweekly sample data over Herdade da Mitra and Serra de Ossa field sites to evaluate fuel moisture time series and compare them with remote sensing data from satellites, such as Sentinel-2 and Landsat-8.