MO3.M1.2

Improving Forest Burned Area Mapping Using Weak Labels and Probabilistic Deep Learning

Benyamin Hosseiny, School of Surveying and Geospatial Engineering, Faculty of Engineering, Iran; Pouria Ramzi, Department of Primary Industries and Regional Development, Australia; Saeid Homayouni, Centre Eau Terre Environnement, Canada

Session:
MO3.M1: New Frontiers in Satellite Remote Sensing for Geohazard Monitoring: Advanced Algorithms to Real-world Applications I Oral

Track:
Community-Contributed Sessions

Location:
Room M1

Presentation Time:
Monday, 4 August, 13:15 - 13:30

Session Co-Chairs:
Pietro Mastro , IREA-CNR and Antonio Pepe, IREA-CNR
Presentation
Discussion
Resources
No resources available.
Session MO3.M1
MO3.M1.1: A universal adapter in segmentation models for transferable landslide mapping
Ruilong Wei, Institute of Mountain Hazards and Environment, China; Yamei Li, Institute of Tibetan Plateau Research, China; Yao Li, Tsinghua University, China; Bo Zhang, Jiao Wang, Chunhao Wu, Institute of Mountain Hazards and Environment, China; Shunyu Yao, China Institute of Water Resources and Hydropower Research, China; Chengming Ye, Chengdu University of Technology, China
MO3.M1.2: Improving Forest Burned Area Mapping Using Weak Labels and Probabilistic Deep Learning
Benyamin Hosseiny, School of Surveying and Geospatial Engineering, Faculty of Engineering, Iran; Pouria Ramzi, Department of Primary Industries and Regional Development, Australia; Saeid Homayouni, Centre Eau Terre Environnement, Canada
MO3.M1.3: DROUGHT CAUSAL ANALYSIS BASE ON REMOTE SENSING DATA AND DEEP NEURAL NETWORKS
Ming Wang, Lei He, Han Luo, Chengdu University of Information Technology, China; Yuxia Li, University of Electronic Science and Technology of China, China; Yunhao He, Yuheng Lei, Chengdu University of Information Technology, China
MO3.M1.4: IMPACT OF SAMPLE ALLOCATION ON FLOOD CLASSIFICATION USING SYNTHETIC APERTURE RADAR AND RANDOM FORESTS
Paul Hosch, Antara Dasgupta, RWTH Aachen Universität, Germany
MO3.M1.5: Generating Electromagnetic Satellite Synthetic Data for Detecting Seismic Precursors
Yaxin Bi, Ulster University, United Kingdom; Wei Zhai, Gansu Earthquake Agency, China; Maja Pavlovic, Ulster University, United Kingdom
Resources
No resources available.