A multidecadal satellite-derived burn severity atlas for Portugal (1984 – 2022)

Abstract

Wildfires have been known as one of the most disturbing phenomena in Portugal during last decades with increasing frequency, annual number of ignition and affected area. However, the extent of wildfire-induced changes on soil and vegetation, or burn severity, of these historical wildfires is unclear. To contribute to a better knowledge of post-fire impacts, this study presents a long-term burn severity atlas of historical wildfires in Portugal from 1984 to 2022 using satellite data. Burn perimeters and start/end dates for large wildfires (>=100ha) were gathered and necessary corrections were manually applied on them. Due to the availability of satellite images, different imagery from Landsat sensors were used for different years: Landsat-5 (TM) for 1984 to 2011, Landsat-7 (ETM+) for 2002, and Landsat8 (OLI) for 2013 to 2022. The time lag between wildfire occurrence and satellite image acquisition dates was quantified and used to determine the suitability of each satellite image to estimate burn severity. Then, using Google Earth Engine API (JavaScript) and through a semi-automated process, the burn severity of each wildfire was calculated via difference normalized burn ratio (dNBR) derived indices (dNBR, relative dNBR (RdNBR), Relativized Burn Ratio (RBR), dNBR – Enhanced Vegetation index (dNBR-EVI)). These maps were created by the application of a pair of pre- and post-fire images with the highest suitability values. The analysis performed on the time lag quantification showed a decrease in dNBR accuracy with the increase of both pre- and post-fire time lags. Over 3.7 million ha of land burned in Portugal from 1984 to 2022 in all vegetation types, around 3.2 million were associated with wildfires equal or larger than 100ha with known start and end dates (86.2%). Among these wildfires, 3.1 million ha had dNBR estimates (83.72% of all wildfires and 97.05% of wildfires>=100ha). To the best of our knowledge, a long-term burn severity atlas has never been developed for an entire European country before. Another noteworthy advancement provided by this atlas is that the imageries from Landsat family of sensors were utilized for development of burn severity maps, offering the resolution of 30m over the manually corrected historical wildfire data (perimeters, locations, and dates). Also, a semi-automated process has been provided, equipped with the capacity to develop burn severity atlas for historical wildfires of any other region in the world with the prerequisite of wildfire data. Such datasets can be used by both scientific and management communities to improve current knowledge on post-fire impacts and develop better pre- and post-fire management plans to mitigate wildfire impacts. Moreover, this multidecadal burn severity dataset can be used by other research communities in the fields related to water, soil, and air quality which are potentially at risk due to wildfire occurrences. Acknowledgements We acknowledge CESAM by the Portuguese Foundation for Science and Technology FCT/MCTES (UIDP/50017/2020+UIDB/50017/2020+LA/P/0094/2020). D. Jahanianfard is supported by the Portuguese Foundation for Science and Technology (FCT-Fundação para a Ciência e Tecnologia) with a PhD grant reference (2021.08094.BD). O. Gonzalez-Pelayo further acknowledges FCT for the funding of FRISCO (PCIF/MPG/0044/2018) and SOILCOMBAT (PTDC/EAM-AMB/0474/2020) projects.