MO4.P6: Advances in Machine Learning for Agricultural Land Use and Land Cover Classification II
Monday, 4 August, 15:45 - 17:00
Location: Plaza: Room P6
Session Type: Oral
Session Co-Chairs: Kathryn Sheffield, Department of Energy, Environment and Climate Action and Sabah Sabaghy, Agriculture Victoria
Track: Community-Contributed Sessions
Mon, 4 Aug, 15:45 - 16:00

MO4.P6.1: Automated In-Season Crop-Type Data Layer Mapping Without Ground Truth for the Conterminous United States Based on Multisource Satellite Imagery
Hui Li, Liping Di, Chen Zhang, Li Lin, George Mason Universitty, United States; Liying Guo, George Mason University, United States; Eugene Yu, George Mason Universitty, United States; Zhengwei Yang, U.S. Department of Agriculture, United States
Mon, 4 Aug, 16:00 - 16:15

MO4.P6.2: FARMLAND CHANGE MONITORING USING MULTI-TEMPORAL SAR DATA WITH DEEP LEARNING
Chaowei Jiang, Chao Wang, Fan Wu, Lu Xu, Nan Chen, Tianyang Li, Yixian Tang, Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, China
Mon, 4 Aug, 16:15 - 16:30

MO4.P6.3: Long-term (2013–2022) mapping of winter wheat in the North China Plain using Landsat data: classification with optimal zoning strategy
Yifei Liu, Xuehong Chen, Jin Chen, Yunze Zang, Beijing Normal University, China; Jingyi Wang, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, China; Miao Lu, Liang Sun, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, China; Qi Dong, Beijing Normal University, China; Bingwen Qiu, Fuzhou University, China; Xiufang Zhu, Beijing Normal University, China
Mon, 4 Aug, 16:30 - 16:45

MO4.P6.4: 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
Mon, 4 Aug, 16:45 - 17:00

MO4.P6.5: 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