Frontiers in Agricultural and Energy Data Collection and Application
There is an exciting emergence of new technologies and tools for data collection and decision making in agriculture, such as the use of unmanned aircraft systems (UASs - drones) for precision monitoring. And not just in yield or performance monitoring, but also in collecting data for climate resilience, adaptation and mitigation in agricultural environments. These new frontiers of data collection also open up questions about data stewardship, and often times bring people into the “big data” fold that have little prior experience.
Specific Topic Focus:
Data Collection Technologies - Unmanned Aircraft Systems (UASs - drones)
Applications / Techniques / Tools - Monitoring Agricultural Activity, Landuse Change and Climate Indicators
Session Schedule:
Introduction: The Landscape of Emerging Frontiers in Agricultural Data Collection (Lindsay Barbieri will provide Introduction)
Brief Overview of "New Frontiers" in Agriculture Unmanned Aircraft Systems in Agriculture
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Monitoring Deforestation, Agriculture and Landuse - Max Messinger
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USDA Use of Unmanned Aircraft Systems (UASs) - Ray Hunt, USDA
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Agricultural Activity and Greenhouse Gas Emissions - Lindsay Barbieri
Discussion: “Big Data” Users and Creators in these New Frontiers and exploring the connections with ESIP and Data Science more broadly. Data Examples: Irregular nature of drone data: time, space, mode of collection, formats, metadata model, etc.
USDA Use of Small Unmanned Aircraft Systems (sUAS)
Raymond Hunt
Over the last 60 years, record agricultural yields have been reached year after year
However, due to human development, we still need to grow more food on less land
Agricultural production increases often lead to poor environmental quality.
How to increase these efficiencies?
- Precision farming!
- Using GPS and GIS
- Apply variable amounts of fertilizer and pesticides
How do you determine plant requirements???
- Yield monitors, which account for 50-75% of the variance in fertilizer requirements
It’s important to note that other (non drone) tech is available: Sensors, robot tractors, etc
Aerial photographs are already used
- UAS needs to provide better information
Examples:
- Field studies at OSU
- Japanese fertilizer application
- Potato damage monitoring from potato beetles
- Investigate irrigation efficiency
- Fire monitoring by the forest service
- Identify invasive species in New Mexico
Needs from ESIP:
- big data (Huge data files (small is 100s of GB))
- computer vision
Monitoring Agricultural Emissions
Lindsay Barbieri
Agriculture is an important factor in climate change
FUNding Friday funded a CO2 monitor.
This study: hay field monitoring
- related to water quality
- impact on GHG emissions
Fields managed for improved water quality are often worse in terms of GHG emissions
Drones can help:
- Higher resolution than satellites
- Can resolve microtopographies
- Can target specific events much better
How can ESIP help?
- Data sharing and collaboration
- Potential links ot the disaster cluster
Using unmanned aircraft to provide near real-time updates of biomass, forest structure, and land use in the Western Amazon
A new look at an old problem
Max Messinger
Forest cover is important for the climate system and biodiversity
Satellite data are limited
- Can detect deforestation
- Struggle to tell us the cause of deforestation
Manned aircraft are super expensive
Drones are the solution (surprise)
One of the major issues with deforestation in Peru is enforcement of the laws
- not enough information
- UAVs can help!
When combined with a single lidar overpass, can monitor canopy height with time.
- This can also lead to carbon density monitoring
Current work: Forest loss and disturbances
- Get carbon baselines
- Estimate carbon lost
- Track disturbances
Data Challenges
- 200 GB/day
- 40 TB/year
- need 10-15 TFLOPS of processing
- Distribute in near real time
- With bad power and low bandwidth
Notes from Bill Teng
3 sessions related to drones and drone data (sponsoring ESIP group)
- Place of drones and drone data in ESIP: Drone data interpretation, management, format, standards, cataloging, discovery
- Most drone data are dark data.
- Used for education (college, K-12), applications, research
- USDA ARS program on UAV
- Focus on increasing efficiency
- Selective application of pesticides and fertilizers (UAV onboard processing of NDVI to determine soil/crop and then targeted spray)
- UAVs for 3 D’s (dull, dark, and dangerous)
| Attachment | Size |
|---|---|
 Ag Session.pptx | 33.98 MB |
| Barbieri ESIP- Drones, Ag, Climate.pptx | 27.61 MB |
 hunt_UAS-precision-ag_esip-winter-2016.pdf | 6.26 MB |