Multi-Scale Coal Fire Detection Based on an Improved Active Contour Model from Landsat-8 Satellite and UAV Images

Underground coal fires can increase surface temperature, cause cracks and collapse, release poisonous harmful gases, which significantly harm the ecological environment humans. Traditional methods of extracting fires, such as global threshold, K-mean active contour model, usually produce many false alarms. Therefore, this paper proposes an improved model by introducing distinguishing energies others into traditional model. Taking Urumqi, Xinjiang, China research area, are detected from Landsat-8 satellite unmanned aerial vehicle (UAV) data. The results show that proposed method eliminate alarms compared with some methods, achieve detection small-area referring field survey More importantly, obtained UAV data help identify not only burning but also potential underground fires. This provides efficient for high-precision fire strong technical support reducing environmental pollution energy use.