B030
Smart Farming and Natural Resource Management Enabled by Remotely Sensed Big Data I

Wednesday, 9 December 2020: 04:00-05:00
Virtual
Primary Convener:  Yun Yang, USDA Beltsville Agricultural Research Center, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States
Conveners:  Martha B. Anderson, USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States, Xiaoyuan Yang, The Climate Corporation San Francisco, San Francisco, CA, United States and Zhe Zhu, University of Connecticut, Department of Natural Resources and the Environment, Storrs, CT, United States
Primary Liaison:  Yun Yang, University of Maryland College Park, ESSIC, College Park, MD, United States
Chairs:  Yun Yang, University of Maryland College Park, ESSIC, College Park, MD, United States, Martha B. Anderson, USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States and Zhe Zhu, University of Connecticut, Department of Natural Resources and the Environment, Storrs, CT, United States
OSPA Liaison:  Zhe Zhu, University of Connecticut, Department of Natural Resources and the Environment, Storrs, CT, United States
04:00
Mapping Crop Emergence at Sub-field Scales Using PlanetScope Imagery (Invited) (665391)
Feng Gao, USDA-Agricultural Research Service Beltsville, Hydrology and Remote Sensing, Beltsville, MD, United States, Martha B. Anderson, USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States, Rasmus Houborg, Planet Labs, San Francisco, United States and Yanghui Kang, USDA ARS, Hydrology and Remote Sensing Lab, Beltsville, MD, United States
04:04
Combining Model Predictions with Satellite Data to Improve Agricultural Water Use and Nutrient Management (Invited) (666093)
Xin-Zhong Liang, University of Maryland College Park, Department of Atmospheric & Oceanic Science, College Park, MD, United States
04:08
CubeSat Enabled Sensor Fusion Approach for Daily Mapping of In-field Leaf Area Index (701296)
Rasmus Houborg1, Arin Jumpasut2, Ignacio Zuleta2 and Tim Schaub2, (1)Planet Labs, San Francisco, CA, United States, (2)Planet Labs, San Francisco, United States
04:12
Generating MODIS-consistent High-resolution Leaf Area Index for Landsat and Sentinel-2 with a Data-driven Approach (685727)
Yanghui Kang, USDA Beltsville Agricultural Research Center, Hydrology and Remote Sensing, Beltsville, WI, United States, Feng Gao, USDA-Agricultural Research Service Beltsville, Hydrology and Remote Sensing, Beltsville, MD, United States, Martha B. Anderson, USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States, Mutlu Ozdogan, University of Wisconsin Madison, Center for Sustainability and the Global Environment, Madison, WI, United States, Tyler Erickson, Google, Earth Outreach, Mountain View, CA, United States, Yun Yang, USDA Beltsville Agricultural Research Center, Hydrology and Remote Sensing Laboratory, Beltsville, MD, United States and Yang Yang, USDA ARS, Hydrology and Remote Sensing Laboratory, Beltsville, Maryland, United States
04:16
Filling the soil data gap (713137)
Jonathan Sanderman1, Shree R.S. Dangal1, Kathe E Todd-Brown2, Tomislav Hengl3, Richard R. Ferguson4, Yufeng Ge5, Charlotte Rivard1, Fenny M van Egmond6, Kathleen E Savage1, Keith Shepherd7, Nuwan Wijewardane8 and Lucrezia Caon9, (1)Woods Hole Research Center, Falmouth, MA, United States, (2)University of Florida, Ft Walton Beach, FL, United States, (3)OpenGeoHub Foundation, Wageningen, Netherlands, (4)National Soil Survey Center, Lincoln, United States, (5)University of Nebraska Lincoln, Department of Biological Systems Engineering, Lincoln, NE, United States, (6)ISRIC - World Soil Information, Wageningen, Netherlands, (7)World Agroforestry Centre (ICRAF), Nairobi, Kenya, (8)University of Nebraska Lincoln, Lincoln, NE, United States, (9)Food and Agriculture Organization of the United Nations, Rome, Italy
04:20
Land disturbance characterization based on Landsat time series (702880)
Shi Qiu, University of Connecticut, Department of Natural Resources and the Environment, Groton, CT, United States and Zhe Zhu, University of Connecticut, Department of Natural Resources and the Environment, Storrs, CT, United States
04:24
Innovative Application of CubeSat Imagery to Predict Wheat Yield Without Ground-Based Data (714873)
Yuval Sadeh1, Xuan Zhu2, David Dunkerley2, Jeffrey P Walker3 and Karine Chenu4, (1)Monash University, School of Earth, Atmosphere and Environment, Melbourne, VIC, Australia, (2)Monash University, School of Earth, Atmosphere and Environment, Clayton, VIC, Australia, (3)Monash University, Department of Civil Engineering, Clayton, VIC, Australia, (4)The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Toowoomba, QLD, Australia
04:28
Mapping sugarcane plantation dynamics in Guangxi, China, by time series Sentinel-1, Sentinel-2 and Landsat images (761049)
Jie Wang, University of Oklahoma Norman Campus, Department of Microbiology and Plant Biology, Center for Spatial Analysis, Norman, OK, United States, Xiangming Xiao, Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, United States, Luo Liu, South China Agricultural University, Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou, China, Xiaocui Wu, University of Oklahoma, Department of Microbiology and Plant Biology, Norman, OK, United States, Yuanwei Qin, University of Oklahoma, Norman, OK, United States, Jean L. Steiner, USDA ARS, Manhattan, United States; Kansas State University, Adjunct, Manhattan, KS, United States and Jinwei Dong, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
04:32
Discussion
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