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

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

3. 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

4. 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

5. 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,…)

6. 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

8. 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 521nm, 543nm, 618nm, 672nm, 761nm, and 785nm (Si-range)
5-band
MicaSense imagery
2. Down-welling light sensor for calibration