Tiago M. Oliveira

Assessing the effect of a fuel break network to reduce burnt area and wildfire risk transmission

Wildfires pose complex challenges to policymakers and fire agencies. Fuel break networks and area-wide fuel treatments are risk-management options to reduce losses from large fires. Two fuel management scenarios covering 3% of the fire-prone Algarve region of Portugal and differing in the intensity of treatment in 120-m wide fuel breaks were examined and compared with the no-treatment option. We used the minimum travel time algorithm to simulate the growth of 150 000 fires under the weather conditions historically associated with large fires. Fuel break passive effects on burn probability, area burned, fire size distribution and fire transmission among 20 municipalities were analysed. Treatments decreased large-fire incidence and reduced overall burnt area up to 17% and burn probability between 4% and 31%, depending on fire size class and treatment option. Risk transmission among municipalities varied with community. Although fire distribution shifted and large events were less frequent, mean treatment leverage was very low (1 : 26), revealing a very high cost–benefit ratio and the need for engaging forest owners to act in complementary area-wide fuel treatments. The study assessed the effectiveness of a mitigating solution in a complex socioecological system, contributing to a better-informed wildland fire risk governance process among stakeholders.

Mapping shrublands and forests with multispectral satellite images based on spectral unmixing of scene components

Linear spectral mixture models (SMM) with image endmembers (IEM) and with reference endmembers (REM) were tested for discriminating maritime pine stands and shrublands in a Landsat-TM image of Central Portugal. For both types of EM, IEM and REM, two types of SMM were tried: SMM with three EM (SMM-3), i.e., green vegetation, soil and shade, and SMM with five EM (SMM-5), where the EM were the components of the landscapes that we were interested on, i.e., pine canopy, shrub, soil, forest litter and shade. Results showed that in the SMM-5, REM need to be used, since IEM were not pure enough. We verified that in the SMM-5, there was not a single set of EM that could be applied to the whole study area, because the shrubs that exist underneath the pine canopy and in the shrublands could not be modeled just by using a shrub EM. Therefore, SMM-5 require a multi-endmember approach, where the set of EM may change from pixel to pixel. In the SMM-3, an accurate discrimination of shrublands and pine stands (90% accuracy) was achieved by thresholding the shade fraction. In these simpler SMM, IEM and REM produced similar results.