1211 | 748 | 20 years of Iberian wildfires: A remote sensing approach from MODIS data. | Víctor Gil Ortega (1), Achim Röder (2), Beatriz Duguy (1)

The Iberian Peninsula has experienced an increase in the frequency and severity of wildfires in recent decades, leading to significant ecological, economic, and social consequences. Remote sensing data, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), have been widely used to monitor and analyze wildfire patterns and their associated factors. In this research, remote sensing data from MODIS and ignition points from 2000 to 2020 were used to investigate the relationship between wildfire occurrence and ecological and anthropogenic factors in the Iberian Peninsula._x000D_
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The results of the analysis show that burned area MODIS data can provide valuable information on wildfire patterns and their association with climatic factors, such as temperature, precipitation and wind as well as ecological parameters as land cover and anthropogenic factors as population density, land uses or roads. In addition, we compared this data with different government datasets on wildfire occurrence and found that they generally agreed on the spatial and temporal patterns of wildfires, but there were some discrepancies in the number and size of fires. These discrepancies may be due to differences in data sources and classification methods used by the government and remote sensing data._x000D_
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Overall, the research highlights the importance of using remote sensing data in monitoring and analyzing wildfire patterns and their associated factors in a fire-threatened region as the Iberian Peninsula. The comparison between remote sensing data and governments data provides insights into the strengths and limitations of different data sources and classification methods, which can be used to improve wildfire management and prevention strategies considering heterogeneity in wildfire drivers across the different regions.

Víctor Gil Ortega (1), Achim Röder (2), Beatriz Duguy (1)
(1) Department of Evolutive Biology, Ecology and Environmental Sciences, University of Barcelona, Spain. (2) Department of Environmental Remote Sensing and Geoinformatics, University of Trier, Germany.
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