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
Session:
WE4.R18: Forest and Vegetation VI Oral
Track:
Land Applications
Location:
Monroe
Presentation Time:
Wednesday, 12 August, 16:15 - 16:30
Session Chair:
Fuzhong Weng, Nanjing University of Information Science and Technology
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
WE4.R18.2: Leveraging GEDI waveform lidar for next-generation fire behavior modeling
Birgit Peterson, US Geological Survey; Seth Price, KBR; Ethan Ilse, C2G; Katelyn Woolfrey, KBR
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; Johan E.S. Fransson, Linnaeus University
WE4.R18.4: A HYDRAULIC FOREST MODEL DRIVEN BY TOMOGRAPHIC RADAR AT P-BAND
Patrik J. Bennet, Albert R. Monteith, Chalmers University of Technology; Jose Gutierres Lopez, Swedish University of Agricultural Sciences; Lars M. H. Ulander, Chalmers University of Technology
WE4.R18.5: EVALUATION OF MICROWAVE LAND EMISSIVITY MODEL USING GROUND-BASED MEASUREMENTS
YiDan Wang, Nanjing University of Information Science and Technology; WenYing He, Institute of Atmospheric Physics, Chinese Academy of Sciences; Fuzhong Weng, CMA Earth System Modeling and Prediction Centre; MinZheng Duan, Institute of Atmospheric Physics, Chinese Academy of Sciences
Resources
No resources available.