Fuel load characterization using remote sensing data over Alentejo, Portugal

Abstract

Fire is a worldwide and complex phenomenon with a critical role in water and carbon cycles. Furthermore, future scenario projections denote that Portugal will be warmer and drier than nowadays due to climate changes. Therefore, it is essential to understand the vegetation dynamic and fire susceptibility. In such a context, remote sensing allows extensive area coverage and temporal regularity and can be helpful for a better understanding of surface vegetation representation. In the PyroC.pt project, one goal aims to improve the fuel load and moisture content representation through satellite data. For this work, we used two above-ground biomass (AGB) datasets: first, samples collected by “Instituto da Conservação da Natureza e das Florestas” (ICNF) in 2015 for the Portuguese National Forest Inventory; and second, AGB derived from ~3.000 trees in-situ dendrometric variables measurements (total height, tree diameter at 1.30m above the ground) on field site in the Herdade da Mitra at the University of Evora for 2021. Also, we are collecting biweekly sample data to estimate fuel moisture content over two field sites in order to compare with remote sensing data from satellites, such as Sentinel-2 and Landsat-8. In addition, we used drone imagery from DJI Phantom 4 Multispectral, which has six spectral bands, including an infrared channel.