Wildfire Detection

Wildfire detection research focuses on rapidly and accurately identifying wildfires using diverse data sources, primarily satellite imagery and drone-captured video and thermal data, to enable timely intervention and mitigation efforts. Current research emphasizes the application of deep learning models, including convolutional neural networks (CNNs) and transformer architectures, often enhanced by techniques like self-supervised learning and domain adaptation to improve accuracy and efficiency, even with limited labeled data. These advancements are crucial for improving wildfire management strategies, enhancing predictive modeling of fire spread, and ultimately reducing the devastating environmental and economic consequences of wildfires.