A deep learning model using geostationary satellite data for forest fire detection with reduced detection latency

• Published in: GIScience and remote sensing Vol. 59; no. 1; pp. 2019 - 2035
• Main Authors: Kang, Yoojin, Jang, Eunna, Im, Jungho, Kwon, Chungeun
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 31.12.2022; Taylor & Francis Group
• Subjects: algorithms; convolutional neural network; fire detection; Forest fire; forest fires; forests; Himawari-8 AHI; machine learning; neural networks; random forest; remote sensing; satellites; spatial data; statistical analysis

Although remote sensing of active fires is well-researched, their early detection has received less attention. Additionally, simple threshold approaches based on contextual statistical analysis suffer from generalization problems. Therefore, this study proposes a deep learning-based forest fire dete...