In recent years, the world witnessed many devastating wildfires, most recently in Australia, that resulted in destructive human and environmental impacts across the globe. Emergency response and rapid response for mitigation call for effective approaches for near real-time wildfire monitoring. Capable of penetrating clouds and smoke, and imaging day and night, Synthetic Aperture Radar (SAR) can play a critical role in wildfire monitoring.
Yifang Ban, KTH Professor and her team, Puzhao Zhang, her PhD student and Dr Andrea Nascetti, Research Scientist at Division of Geoinformatics, investigated and demonstrated the potential of Sentinel-1 SAR time series with a deep learning framework for near real-time wildfire progression monitoring.
In collaboration with researchers from Canadian Forest Services and British Columbia Ministry of Forests, Lands, Natural Resource Operations and Rural Development in Canada, their results are published in the journal Nature Scientific Reports entitled ‘Near Real-Time Wildfire Progression Monitoring with Sentinel-1 SAR Time Series and Deep Learning’.
