WE1.R2.1

MAPPING CALIFORNIA RICE USING OPTICAL AND SAR DATA FUSION WITH PHENOLOGICAL FEATURES IN GOOGLE EARTH ENGINE

Wenzhao Li, Hesham El-Askary, Daniele Struppa, Chapman University, United States
Session:
WE1.R2: Multisensor Fusion Oral
Track:
Data Analysis
Location:
Room C
Presentation Time:
Wed, 19 Jul, 08:30 - 08:42 Pacific Time (UTC -7)
Session Chair:
Francisco Mena, University of Kaiserslautern-Landau (RPTU)
Session Manager:
Soumitra Sakhalkar
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Session WE1.R2
WE1.R2.1: MAPPING CALIFORNIA RICE USING OPTICAL AND SAR DATA FUSION WITH PHENOLOGICAL FEATURES IN GOOGLE EARTH ENGINE
Wenzhao Li, Hesham El-Askary, Daniele Struppa, Chapman University, United States
WE1.R2.2: SURE-ERGAS: UNSUPERVISED DEEP LEARNING MULTISPECTRAL AND HYPERSPECTRAL IMAGE FUSION
Han V. Nguyen, Magnus O. Ulfarsson, Johannes R. Sveinsson, University of Iceland, Iceland; Mauro Dalla Mura, Grenoble Institute of Technology, France
WE1.R2.3: MULTI-SENSOR FUSION FOR SIMULTANEOUS GEOMETRIC-PHYSICS MODELING OF ENVIRONMENT
Su Zhang, Haoyu Chen, Minchao Zhang, Kai Tan, Haipeng Wang, Feng Xu, Fudan University, China
WE1.R2.4: A COMPARATIVE ASSESSMENT OF MULTI-VIEW FUSION LEARNING FOR CROP CLASSIFICATION
Francisco Mena, University of Kaiserslautern-Landau (RPTU), Germany; Diego Arenas, Marlon Nuske, Andreas Dengel, German Research Center for Artificial Intelligence (DFKI), Germany
WE1.R2.5: GEDI AND SENTINEL-2 INTEGRATION FOR MAPPING COMPLEX WETLANDS
Sarina Adeli, SUNY College of Environmental Science and Forestry, United States; Lindi J. Quackenbush, State University of New York, College of Environmental Science and Forestry, United States; Bahram Salehi, SUNY College of Environmental Science and Forestry, United States; Masoud Mahdianpari, C-CORE and Memorial University of Newfoundland, Canada
Resources
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