MO4.P1.3
MITIGATING UNDERESTIMATION OF FIRE EMISSIONS FROM THE ADVANCED HIMAWARI IMAGER: A MACHINE LEARNING AND MULTI-SATELLITE ENSEMBLE APPROACH
Yoojin Kang, Jungho Im, Ulsan National Institute of Science and Technology, Korea (South)
Session:
MO4.P1: Improved Characterization and Understanding of Wildfires and their Environmental Impacts using Satellite Data and Artificial Intelligence II Oral
Track:
Community-Contributed Sessions
Location:
Plaza: Room P1
Presentation Time:
Monday, 4 August, 16:15 - 16:30
Session Chair:
Yoojin Kang, Ulsan National Institute of Science & Technology
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Session MO4.P1
MO4.P1.1: FOREST WILDFIRE DETECTION BASED ON GEO-KOMPSAT-2A REMOTE SENSING IMAGERY DATA AND FUEL MOISTURE CONTENT
Jingyu Zhang, Rui Jiang, University of Electronic Science and Technology of China, China
MO4.P1.2: PRE- AND POST-FIRE AIRBORNE LIDAR TO QUANTIFY CANOPY AND GROUND BIOMASS COMBUSTION FOLLOWING FIRE IN A PERMAFROST-PEATLAND COMPLEX
Laura Chasmer, Linda Flade, Emily Jones, Kailyn Nelson, University of Lethbridge, Canada; William Quinton, Wilfrid Laurier University, Canada; Chris Hopkinson, University of Lethbridge, Canada
MO4.P1.3: MITIGATING UNDERESTIMATION OF FIRE EMISSIONS FROM THE ADVANCED HIMAWARI IMAGER: A MACHINE LEARNING AND MULTI-SATELLITE ENSEMBLE APPROACH
Yoojin Kang, Jungho Im, Ulsan National Institute of Science and Technology, Korea (South)
MO4.P1.4: LIVE FUEL MOISTURE CONTENT FORECASTING BY INTEGRATING REMOTE SENSING AND WEATHER DATA
Qinglong Jia, Xingwen Quan, University of Electronic Science and Technology of China, China
Resources
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