WE4.R18.3
FROM MULTI-MODAL SENTINEL FEATURES TO FOUNDATION EMBEDDINGS: RETRIEVAL OF FOREST DIAMETER AT BREAST HEIGHT USING SWEDISH NATIONAL FOREST INVENTORY DATA AND MACHINE LEARNING
Samet Aksoy, Elif Sertel, Istanbul Technical University, Türkiye; Johan E.S. Fransson, Linnaeus University, Sweden
Session:
WE4.R18: Forest and Vegetation VI Oral
Track:
Land Applications
Location:
TBD
Presentation Time:
Wed, 12 Aug, 16:45 - 17:00
Presentation
Discussion
Resources
No resources available.
Session WE4.R18
WE4.R18.1: Characterizing Coastal Forest Change Using Landsat Time Series and Aerial Images with Deep Learning
Yuwei Fu, Zijun Yang, University of North Carolina Wilmington, United States
WE4.R18.2: Leveraging GEDI waveform lidar for next-generation fire behavior modeling
Birgit Peterson, US Geological Survey, United States; Seth Price, KBR, United States; Ethan Ilse, C2G, United States; Katelyn Woolfrey, KBR, United States
WE4.R18.3: FROM MULTI-MODAL SENTINEL FEATURES TO FOUNDATION EMBEDDINGS: RETRIEVAL OF FOREST DIAMETER AT BREAST HEIGHT USING SWEDISH NATIONAL FOREST INVENTORY DATA AND MACHINE LEARNING
Samet Aksoy, Elif Sertel, Istanbul Technical University, Türkiye; Johan E.S. Fransson, Linnaeus University, Sweden
WE4.R18.4: A HYDRAULIC FOREST MODEL DRIVEN BY TOMOGRAPHIC RADAR AT P-BAND
Patrik J. Bennet, Albert R. Monteith, Lars M. H. Ulander, Chalmers University of Technology, Sweden
Contacts