MO3.PZ.5
Explainable AI for Wetland Mapping Using High Resolution Remote Sensing Data
Mohammad Marjani, Masoud Mahdianpari, Eric W. Gill, Memorial University of Newfoundland, Canada; Fariba Mohammadimanesh, Natural Resources Canada, Canada
Session:
MO3.PZ: Student Paper Competition I Oral
Track:
Student Paper Competition
Location:
Plaza Room
Presentation Time:
Monday, 4 August, 13:00 - 13:00
Presentation
Discussion
Resources
No resources available.
Session MO3.PZ
MO3.PZ.5: A NOVEL AND PRACTICAL APPROACH TO GENERATE ALL-WEATHER 30-METER LAND SURFACE TEMPERATURE DATA
Shengjie Liu, Lu Zhang, Siqin Wang, University of Southern California, United States
MO3.PZ.5: Validation of a new airborne snow radar on Antarctic sea ice
Pauline Barras, University of Canterbury, New Zealand; Adrian Eng-Choon Tan, Lincoln Agritech Ltd, New Zealand; Wolfgang Rack, University of Canterbury, New Zealand; Christian Haas, Alfred Wegener Institute, Germany; Inga Smith, University of Otago, New Zealand; Sean Minhui Tashi Chua, Nansen Environmental and Remote Sensing Center, Norway; Shelley MacDonell, Daniel Price, University of Canterbury, New Zealand
MO3.PZ.2: EARLY WARNING OF TSUNAMIS INTEGRATING ANOMALY DETECTION INFORMATION FROM HFSWR AND GNSS
Menghua Jiang, Yonggang Ji, Ruozhao Qu, Yahui Chen, China University of Petroleum (East China), China; Changjun Yu, Harbin Institute of Technology at Weihai, China
MO3.PZ.2: PROPOSAL OF A CONTEXT-AWARE POLSAR FILTER BASED ON QUATERNION WAVELET SHRINKAGE FOR EFFICIENT LAND COVER CLASSIFICATION
Yuta Otsuka, Ryo Natsuaki, Akira Hirose, The University of Tokyo, Japan
MO3.PZ.5: Explainable AI for Wetland Mapping Using High Resolution Remote Sensing Data
Mohammad Marjani, Masoud Mahdianpari, Eric W. Gill, Memorial University of Newfoundland, Canada; Fariba Mohammadimanesh, Natural Resources Canada, Canada
Resources
No resources available.