TH1.R7.1

FOREST HEIGHT ESTIMATION USING MULTI-FREQUENCY SAR AND A STACKING REGRESSION

João E. Pereira-Pires, School of Science and Technology, NOVA University of Lisbon and University of Surrey, Portugal; João M. N. Silva, School of Agriculture, University of Lisbon, Portugal; José M. Fonseca, André Mora, School of Science and Technology, NOVA University of Lisbon, Portugal; Raffaella Guida, University of Surrey, United Kingdom
Session:
TH1.R7: Machine Learning for Forest Monitoring Oral
Track:
Community-Contributed Sessions
Location:
Room G
Presentation Time:
Thu, 20 Jul, 08:30 - 08:42 Pacific Time (UTC -7)
Session Co-Chairs:
Qian Song, Technical University of Munich and Xiao Wang, Nanjing Tech University
Session Manager:
Al Adil Al Hinai
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Session TH1.R7
TH1.R7.1: FOREST HEIGHT ESTIMATION USING MULTI-FREQUENCY SAR AND A STACKING REGRESSION
João E. Pereira-Pires, School of Science and Technology, NOVA University of Lisbon and University of Surrey, Portugal; João M. N. Silva, School of Agriculture, University of Lisbon, Portugal; José M. Fonseca, André Mora, School of Science and Technology, NOVA University of Lisbon, Portugal; Raffaella Guida, University of Surrey, United Kingdom
TH1.R7.2: 3D POINT CLOUD SIMULATION FOR ABOVE-GROUND FOREST BIOMASS ESTIMATION
Qian Song, Yuanyuan Wang, Xiao Xiang Zhu, Technical University of Munich, Germany
TH1.R7.3: GENERALIZATION ACROSS SENSOR MODALITIES FOR DEFORESTATION ASSESSMENT
Joana Reuss, Michael Engel, Stephanie Tumampos, Marco Körner, Technical University of Munich, Germany
TH1.R7.4: INVESTIGATING SAR-OPTICAL DEEP LEARNING DATA FUSION TO MAP THE BRAZILIAN CERRADO VEGETATION WITH SENTINEL DATA
Paulo Silva Filho, Aeronautical Institute of Technology, Brazil; Claudio Persello, Raian V. Maretto, Faculty of Geo-Information Science and Earth Observation, University of Twente, Netherlands; Renato Machado, Aeronautical Institute of Technology, Brazil
TH1.R7.5: A DATASET FOR INDIVIDUAL TREE DELINEATION FROM 3D POINT CLOUD DATA
Qian Song, Xiao Xiang Zhu, Technical University of Munich, Germany
Resources
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