THP2.PI.8
TREE CANOPY SEGMENTATION IN LOW-DATA REGIMES USING PRETRAINED DEEP MODELS
David Szczecina, Hudson Sun, Anthony Bertnyk, Niloofar Azad, Kyle Gao, University of Waterloo, Canada; Lincoln Linlin Xu, University of Calgary, Canada
Session:
THP2.PI: Remote Sensing and Geospatial Modeling of Wildfire Risk, Detection, and Recovery Poster
Track:
Community Contributed Themes
Location:
TBD
Presentation Time:
Thu, 13 Aug, 15:00 - 16:15
Presentation
Discussion
Resources
No resources available.
Session THP2.PI
THP2.PI.1: Physics-Based Retrieval of Foliage Fuel Load from Sentinel-2 Imagery Using a Coupled RTM–LUT Approach
Chenglin Zhang, Binbin He, Yuwei Guan, University of Electronic Science and Technology of China, China; Yingjie Tian, Pengfei Xu, Song Wang, Tianjin Key Laboratory of Spatio-Temporallnformation Engineering and Technology, China
THP2.PI.2: MACHINE LEARNING–BASED SHORT-TERM FIRE HAZARD FORECASTING FROM EO AND REANALYSIS DATA
Johanna Wahbe, Sybrand Muller, Kim Feuerbacher, Lukas Liesenhoff, Veronika Pörtge, Julia Gottfriedsen, OroraTech GmbH, Germany
THP2.PI.4: MODELING EFFECTS OF RADIOMETRIC UNCERTAINTIES ON LAND COVER CLASSIFICATION WITH HYPERSPECTRAL DATA
Riyaaz Shaik, Berkshire Hathaway Inc., United States; Afreen Siddiqi, Massachusetts Institute of Technology, United States
THP2.PI.8: TREE CANOPY SEGMENTATION IN LOW-DATA REGIMES USING PRETRAINED DEEP MODELS
David Szczecina, Hudson Sun, Anthony Bertnyk, Niloofar Azad, Kyle Gao, University of Waterloo, Canada; Lincoln Linlin Xu, University of Calgary, Canada
Contacts