Spatiotemporal Burn Severity Evolution Analysis with Identification of most Influential Climatic and Environmental Drivers for Large Fires in Portugal (1984-2022)

There has been an increased prevalence of very large fires in European countries with Mediterranean-type climate where in wet winters vegetation productivity is promoted and in hot dry summers fuel flammability is enabled. Traditionally, the annual burned area (BA) is applied to summarize all attributes related to the fire regime in these regions, reflecting fire management success or failure. However, in Portugal, the most fire-prone country in Europe, no annual BA trend is observed. Many fire-related experts advocate for a shift in this paradigm toward using fire impacts instead of BA, thus, understanding burn severity (BS) is essential to assess impacts and form and implement better pre- and post-fire management plans.

In this study, we analyzed spatiotemporal BS trends for large fires (≥500 ha) in Portugal from 1984 to 2022 with the identification of BS drivers. BS estimates were obtained from the “Portuguese Burn Severity Atlas” using Landsat imagery (30 m) and estimating indices as the difference normalized burn ratio (dNBR), relative dNBR (RdNBR), relative burn ratio (RBR), and dNBR with enhanced vegetation index (dNBR-EVI) to check the coherency of any possible trend via different BS indices. Time series trend was analyzed using different statistics of BS indices. We incorporated climatic and environmental variables to identify the drivers of BS and any possible BS trend. For climatic drivers, all the seven daily Fire Danger Indicators (Fuel Moisture Codes and Fire Behavior Indices) and three hourly weather observation variables from the ERA5 dataset at 15 p.m. as total precipitation, temperature, and vapor pressure deficit were utilized. For environmental drivers, we used: i) the mean elevation obtained by the Digital Elevation Model (30 m) for each fire and ii) vegetation types, for which fires were divided into four macro regimes via the dominant land use and land cover according to Carta de Ocupação do Solo (COS) leading to Pastoral, Urban, Forest, and Agricultural fires. The statistical approaches to conduct both time series analysis and correlation with drivers were based on the simple linear regression, Mann-Kendall test using tau variables, Theil-Sen slope estimator, and Spearman correlation test.

Our analysis revealed a coherent and significant increase in BS over time across all indices except for agricultural fires highlighting that there is a BS evolution in Portugal. While no correlations between climatic drivers and BS trend were found, strong correlations emerged between fuel moisture codes and fire behavior indices with areas with high BS classification, suggesting drier fuels are a key driver. Importantly, annual BA showed no significant relationship with BS, emphasizing the need to shift focus from extent-based metrics to severity-based management.