MOP1.PX.3
MONITORING DIGESTATE APPLICATION ON AGRICULTURAL CROPS USING SENTINEL-2 SATELLITE IMAGERY
Andreas Kalogeras, Dimitrios Bormpoudakis, Iason Tsardanidis, National Observatory of Athens, Greece; Dimitra A. Loka, Hellenic Agricultural Organization (ELGO), Greece; Charalampos Kontoes, National Observatory of Athens, Greece
Session:
MOP1.PX: Advances in Machine Learning for Agricultural Land Use and Land Cover Classification I Poster
Track:
Community-Contributed Sessions
Location:
Poster Area
Presentation Time:
Monday, 4 August, 14:15 - 15:45
Session Chair:
Kathryn Sheffield, Department of Energy, Environment and Climate Action
Presentation
Discussion
Resources
No resources available.
Session MOP1.PX
MOP1.PX.1: Evaluating Dataset Stratification and Uncertainty in Land Cover/Use Classification: Insights from Entropy Analysis
Piero Toscano, National Research Council, Italy; Michele Rinaldi, Sergio Ruggieri, Council for Agricultural Research and Economics, Italy; Alessandro Matese, National Research Council, Italy; Youg-Sin Cheng, Miguel Valdez, Chi-Farn Chen, Nguyen-Thanh Son, National Central University, Taiwan
MOP1.PX.2: IUCN GET Classification Criteria and Designation of Natural Ecosystem Boundaries using Remote Sensing Technology
Haedam Baek, Kyungil Lee, Seonyoung Park, Seoul National University of Science and Technology, Korea (South)
MOP1.PX.3: MONITORING DIGESTATE APPLICATION ON AGRICULTURAL CROPS USING SENTINEL-2 SATELLITE IMAGERY
Andreas Kalogeras, Dimitrios Bormpoudakis, Iason Tsardanidis, National Observatory of Athens, Greece; Dimitra A. Loka, Hellenic Agricultural Organization (ELGO), Greece; Charalampos Kontoes, National Observatory of Athens, Greece
MOP1.PX.4: PROMPTABLE BUILDING SEGMENTATION WITH THE SEGMENT ANYTHING MODEL
Ngoc An Bui, Jangwoo Cheon, Inhyuk Lee, Chong Lee, Juhee Lee, Impyeong Lee, University of Seoul, Korea (South)
MOP1.PX.5: FIELD BY FIELD: MOVING FROM AREA-BASED METRICS TO INSTANCE-LEVEL AGRICULTURAL PARCEL ASSESSMENT
Quentin Yeche, Atos France Technical Services, France; Dino Ienco, Raffaele Gaetano, UMR Tetis, France
MOP1.PX.6: Machine Learning-Based Land Use Classification and Long-Term Projections for Sustainable Resource Management in the Semi-Arid Downstream Merguellil Sub-Basin, Tunisia
Hajer Ataallah, Ines Oueslati, Institut national agronomique de Tunisie, Tunisia; Michel Le Page, University of Toulouse, Center of Spatial studies of the Biosphere, Tunisia; Manel Khlif, Zohra Lili Chabaane, Institut national agronomique de Tunisie, Tunisia
MOP1.PX.7: Advancing Agricultural Land Cover Classification through Machine Learning: Optimizing Data Integration and Validation Strategies
Sabah Sabaghy, Mohammad Abuzar, Doug Crawford, Andy McAllister, Yogendra Karna, Kathryn Sheffield, Agriculture Victoria Research, Australia
MOP1.PX.8: The Victorian Land Use Information System (VLUIS): Data Integration and classification approaches to support the provision of a dynamic and accurate dataset.
Andy McAllister, Kathryn Sheffield, Sabah Sabaghy, Mohammad Abuzar, Yogendra Karna, Doug Crawford, Tony Cook, Department of Energy, Environment and Climate Action, Australia
Resources
No resources available.