10.1594/PANGAEA.955012Neves, Alana KAlana KNeves0000-0002-0301-944XCampagnolo, Manuel LManuel LCampagnoloSilva, João M NJoão M NSilvaPereira, José M CJosé M CPereiraPANGAEA2023Fire mappingLandsat image time seriesPortugalremote sensingDataset10.1016/j.jag.2023.103321136.4 MBytesapplication/zipCreative Commons Attribution 4.0 InternationalThe objectives of this work were to disaggregate the Portuguese Annual Fire Atlas burned area patches into individual events according to their date of occurrence estimated from Landsat temporal series, and to assign them the closest date (day and month) of the detected change. The resulting Monthly Fire Atlas is available from 1984 to 2021 for the entire mainland Portugal. We selected the closest fire date based on the index of the lowest ΔNBR in the time series. The maps were validated using MODIS and VIIRS active fires. Accuracies of individual years fluctuated according to the satellite and cloudiness of each year. For the entire 37 analyzed years, when considering 16 and 32 days of time gap, the Monthly Fire Atlas achieved 84% and 91% of accuracy, respectively. In the raster files, pixel value represents the meanDOY variable, which takes values from 1 (January 1) to 365 or 366. Missing values (NA) indicate that the pixel is not burned.The dataset is composed of three raster files for each year from 1984 to 2021 (37 years).
DOY raster files: pixel values represent the real burned area image Day-Of-Year.
DOYbefore raster files: pixel values represent the Day-Of-Year of previous image.
MeanDOY raster files: pixel values represent the meanDOY variable, calculated based on DOY and DOYbefore raster files.-8.040.0PortugalInstituto Superior de Agronomiahttps://doi.org/10.13039/501100006201UIDB/00239/2020Forest Research CentreUniversidade de Lisboahttps://doi.org/10.13039/501100005765PCIF/GRF/0204/2017FireCast - Forecasting fire probability and characteristics for a habitable pyroenvironment