B126
Utilizing remote sensing data for crop model implementation at regional scales - A potential way forward for data scarce regions
Session ID#: 79825
Session Description:
Agricultural simulation models can be a key component in addressing issues of global food security that includes: monitoring and prediction of agricultural drought and its impacts; yields (production); and agriculture water resources. Crop models typically depend on accurate estimates of numerous inputs which for many areas of the world are typically not available. Sparse weather inputs, in combination with inconsistent management options, tend to increase uncertainties within crop models results. However, some of these uncertainties may be mitigated by utilizing remotely sensed data such as: soil moisture; leaf area index; evapotranspiration; land surface temperature etc. directly or indirectly. In this session, we aim to explore, discuss and put forward research related to the use of earth observation data and models into crop modeling directly (forcing/assimilation) or indirectly (coupled with other land surface model) for improved model performance, particularly in data limited regions of the world at regional scales.
Index Terms:
0402 Agricultural systems [BIOGEOSCIENCES]
0480 Remote sensing [BIOGEOSCIENCES]
1812 Drought [HYDROLOGY]
1847 Modeling [HYDROLOGY]
Primary Convener: Vikalp Mishra, NASA Marshall Space Flight Center, SERVIR/SPoRT, Huntsville, AL, United States
Conveners: Amor V M Ines, Michigan State University, East Lansing, MI, United States, Christopher Hain, NASA Marshall Space Flight Center, Huntsville, AL, United States and Walter Lee Ellenburg, University of Alabama in Huntsville, Huntsville, AL, United States; NASA-SERVIR, Science Coordination Office, Huntsville, AL, United States
Primary Liaison: Vikalp Mishra, NASA Marshall Space Flight Center, SERVIR/SPoRT, Huntsville, AL, United States
Potential for operationalizing a hydro-agricultural modeling and information system: Lessons from Mekong and Eastern Africa regional applications (Invited) (491770)
Konstantinos Andreadis1, Narendra N Das2, Amor V M Ines3, Abhijeet Abhishek3, Susantha Jayasinghe4, Farrukh Chishtie5, Lilian W. Ndungu6 and Walter Lee Ellenburg7, (1)University of Massachusetts Amherst, Civil and Environmental Engineering, Amherst, MA, United States, (2)Jet Propulsion Lab, Pasadena, CA, United States, (3)Michigan State University, East Lansing, MI, United States, (4)Asian Disaster Perpardness Center, SERVIR-Mekong & Climate Resilience, Bangkok, Thailand, (5)SERVIR-Mekong, Bangkok, Thailand, (6)Regional Centre for Mapping of Resources for Development, SERVIR E&SA, Nairobi, Kenya, (7)NASA Marshall Space Flight Center, Huntsville, AL, United States
Bayesian Statistical Calibration of Parameters in the APSIM-Maize Crop Model for Improved Yield Prediction. (509626)
Matteo Giuseppe Ziliani1, Muhammad Umer Altaf1, Trenton E Franz2, Ibrahim Hoteit1 and Matthew McCabe1, (1)King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, (2)University of Nebraska Lincoln, Lincoln, NE, United States
Remotely sensed biophysical variables of wheat as indicators for crop dynamics modelling (520000)
Elena Pareja Serrano1, Jose Gonzalez-Piqueras1, Hatim M.E. Geli2, Alfonso Calera Sr.1 and Andre Chanzy3, (1)Instituto de Desarrollo Regional. Universidad de Castilla-La Mancha, GIS and Remote Sensing Group, Albacete, Spain, (2)New Mexico State University Main Campus, Las Cruces, NM, United States, (3)UMR INRA/UAPV, Environnement Méditerranéen et Modélisation des AgroHydrosystèmes, Avignon, France
Deep-Learning Applications for Time Series SAR (Sentinel-1) Image Classification with Limited Labelled Area (569032)
Hyun-Woo Jo1, Sujong Lee1, Eunbeen Park2, Chul-Hee Lim3, Cholho Song1, Halim Lee1, Youngjin KO4, Sungeun Cha1, Joon Kim1 and Woo-Kyun Lee1, (1)Korea University, Department of Environmental Science and Ecological Engineering, Seoul, South Korea, (2)Korea University, Department of Environmental Science and Ecological Engineering, Seoul, Korea, Republic of (South), (3)Korea University, Institute of Life Science and Natural Resources, Seoul, South Korea, (4)Korea University, Seoul, South Korea
Automated high-resolution spatial yield estimation system with hydrologic root zone modelling using remotely sensed soil moisture assimilation technique (585612)
Nickolay Uvarov1, Nazar Panchii1, Alexei Kryvobok2, Petro Martyniyk3, Nikolay Kovbasa1, Aleksandr Krivoshein2, Elena Kozhushko3, Mikhail Boyko3 and Olga Stepanchenko3, (1)EOS Data Analytics, Kyiv, Ukraine, (2)Ukrainian Hydrometeorological Institute, Kyiv, Ukraine, (3)National University of Water and Environmental Engineering, Rivne, Ukraine
Using in situ Sensor Networks and Remotely Sensed Imagery to Improve Site-Specific Understanding of Maize Yield Variance (591368)
Michael Cecil, Clark University, Worcester, MA, United States, Lyndon D Estes, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States, Tom P Evans, University of Arizona, Tucson, AZ, United States and Adam Wolf, Princeton University, Princeton, NJ, United States
Development of a drought and yield assessment system in Kenya (619220)
Walter Lee Ellenburg II1, Lilian W. Ndungu2, Vikalp Mishra3, Maungu Oware4, Sara Miller5, Faith Mithieu6, Anastasia Mumbi Wahome4 and Robinson M Mugo4, (1)University of Alabama in Huntsville, Huntsville, AL, United States, (2)Regional Centre for Mapping of Resources for Development, SERVIR E&SA, Nairobi, Kenya, (3)University of Alabama, Huntssville, Huntsville, AL, United States, (4)Regional Centre for Mapping of Resources for Development, Nairobi, Kenya, (5)University of Alabama in Huntsville, Middletown, OH, United States, (6)Regional Center for Mapping of Resources for Development, Nairobi, Kenya
Calibration of Crop Growth Simulation Model for Irrigated Cropland Using Remote Sensing Derived Leaf Area Index (622871)
Eugene Yu1, Liping Di2, Md Shahinoor Rahman2, Li Lin2, Haoteng Zhao2, Chen Zhang2 and Junmei Tang3, (1)George Mason University Fairfax, Fairfax, VA, United States, (2)George Mason University, Fairfax, VA, United States, (3)George Mason University, Fairfax, United States
