Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Big Data in Digital Agriculture


Published on

Satellite data and Farmer Information

Published in: Economy & Finance

Big Data in Digital Agriculture

  1. 1. Big Data in Digital Agriculture: Satellite data and Farmer Information Jyothy Nagol Molly E Brown University of Maryland College Park
  2. 2. Disruptive Technologies • Satellite remote has potential to transform agricultural productivity and sustainability. – Design targeted interventions, services, and management strategies • Combined with farmer data, it can help estimate, local to continental scale: – Cropped area, and yield – Yield potential/gap – Climate, and nutrient stresses on yield
  3. 3. Disruptive Technologies • The remote sensing technology is not new – Available since the late 60s • During the last decade it has emerged from mostly governmental use to the commercial and individual domains • The technology is becoming democratized – Open access/ affordable satellite data – Affordable drone technology
  4. 4. Annual Crop Maps • Knowing how cropped area is changing is critical for accurate understanding of food security and prices • Food production α cropped area Changes in Maize cropped area in Zambia
  5. 5. In-Season Yield Monitoring • Determine how weather conditions will affect the ultimate yield of a crop in a particular place/time. - Remote sensing data - Weather, climate, soil data - Crop growth stage models - Machine learning algorithms - Yield outcomes over a range scenarios - Management and climate scenarios. • Determine of whether yields can recover potential levels in the remaining season.
  6. 6. Sowing and Harvest • Identifying the date at which a farmer planted is a critical input to yield monitoring • Delay in the start of season can have significant impact on yield – yield losses of up to one percent per day of delay after the optimum planting date can be experienced. • Remote sensing information can be used to make maps of start and end of the season for yield monitoring
  7. 7. Farm Management is the Key • Each farmer has a different management strategy and resource s at their disposal • Different crop varieties, use of fertilizer, soil inputs, herbicides, pesticides and other products will affect yield • Knowing what the farmer is doing will transform our ability to use high resolution satellite and UAV data
  8. 8. Farmer information can significantly improve the utility of Satellite Data • Digital Agriculture combines multi-source data with machine learning and biogeochemical models to support decision making for individual farmers, agribusiness, and also policy makers. • This can be done through – Engaging with agriculture industry to increase farmer services: • seeds, crop inputs, equipment – Reducing risk through lower cost insurance: • Aggregating farmers into similar risk categories – Delivering of data through mobile devices: • Weather, agronomy, ag products, and market access
  9. 9. How to get Farm Management info? • Surveying the farmer – Digital registries – Accurate, but needs to be updated periodically – High cost, but provides contact information and high level of precision across the landscape • Sampling the farmer strategy using farmer participation and big data analytics. • Using very high resolution data (Satellites/UAVs) to identify farms, then surveying farmers to determine management
  10. 10. Very High Resolution Data from UAVs • UAVs are becoming more and more affordable and useful. • Farmers are turning out to be it’s biggest civilian users. • It has truly democratized remote sensing.
  11. 11. UAVs • UAVs compliment both satellite based remote sensing data as well as farmer information. – Helps link the two levels • Multi-temporal spectral and textural patterns (signatures) can be used to determine crop parameters in a specific field • Higher resolution can achieve clear identification of crop type, crop condition and field boundaries that 10m data cannot
  12. 12. UAVs within an Agriculture Info System • Many affordable online services are available to help data processing
  13. 13. Delivering Value • To improve productivity, digital agriculture must change farmer behavior through information and education • Engaging with farmers through social media, farmer cooperatives, and mobile devices holds promise, with rising mobile connectivity GSMA The mobile industry In Latin America, 2014 2013 data Countries have between 40 – 60% of the population with connections to the Mobile network.
  14. 14. Digital Agriculture • To better understand how farmers can improve yields, we need to have big data for small farmers • Small family farms occupy a large share of the world's agricultural land and produce about 80% of the world's food • Generating high quality information on area cropped, yield estimates, farm management, and delivering knowledge to farmers directly will transform agriculture