WG: Weather, Climate and Agriculture Workshop - Oct. 9, 2018

DAYS/ACRES DECADES/CONTINENTS ? ? ? crop management site selection & design climate-vegetation prediction ? ? ?

decision support tools Example remote ground-based time    SWP   (Cornell/USDA/UC Davis/WSU) analytics stress physiology (apple, grape, almond) distributed SPAC model parameter optimization (hybrid data/mechanism) growth, yield, quality optimal stress & timing forecasts meteorology + climate water & crop pricing decision support tools “digital twin” real-time stress maps stress forecasting soil mapping irrigation design socio-economic anal. e.g., stress map (hourly, 30 m) ROI/cost-benefit analysis barriers for adoption regulatory drivers auto. management model predictive control failure detection

decision support tools Example remote ground-based time      SWP analytics stress physiology (apple, grape, almond) distributed SPAC model parameter optimization (hybrid data/mechanism) growth, yield, quality optimal stress & timing forecasts meteorology + climate resource & crop pricing decision support tools real-time stress maps stress forecasting soil mapping irrigation design “digital twin” socio-economic anal. ROI/cost-benefit analysis barriers for adoption regulatory drivers (Toby Ault et al.) auto. management model predictive control failure detection

DA Challenges Plant physiology + soil science + crop models (Lailiang Cheng, Alan Lakso, Susan Riha, Ying Sun, Harold van Es,…) Sensing technologies (Abe Stroock, Amit Lal, Edwin Kan, David Erickson…) Hydrology + Micrometeorology (Todd Walter, John Albertson, Scott Steinschneider,…) Meteorology + Climate (Art DeGaetano, Toby Ault, Natalie Mahovald,…) Data analytics + System engineering (Fengqi You,…) Economics + Social Science (Miguel Gomez, Steven Wolf,…)

Potential Partners Potential Funding USDA NOAA NASA RIT Remote Sensing Group MS Research Climate Corp … Potential Funding USDA SCRI USDA Center of Excellence NSF Science & Technology Center Gates NYS

UPDATE: RIT - Imaging Science Precision Agriculture UAS Activities Jan van Aardt, Carl Salvaggio, Don McKeown & David Messinger Chester F. Carlson Center for Imaging Science 3. Simulation for corn yield modeling – satellite system specification 1. White mold in snap bean 94% accuracy to detect blooming @ 521nm, 543nm, 618nm, 672nm, 761nm, and 785nm (Si-range) 5-band MicaSense imagery 2. Down-welling light sensor for calibration