Greg Rose, co-founder and vice president of product at IntelinAir, and Ivan Dozier, M.S., senior agronomist, IntelinAir, explore the past, present and future of aerial imagery for agriculture. They discuss the types of imagery available, pros and cons of the various collection methods and why automated analysis is a key component of the usability of aerial imagery.


  • Remote sensing provides a new way to measure crop performance
  • Multispectral lenses offer different perspectives
  • Ability to collect imagery at scale


  • Computer vision & machine learning
  • Combining imagery with data-driven analysis
  • Get to the decision quicker


  • Make in-season decisions to increase yield or reduce costs
  • Better understand factors that drive yield
  • Validate nutrient prescriptions, seed selection, management zones

What are different bands of light?

  • Visible light
    • What your eyes see and what a normal camera can capture
  • Multispectral light
    • These cameras capture imagery in the NIR range
  • Thermal light
    • These cameras measure infrared radiation

Capturing Aerial Imagery

  1. Satellites
    • Pros
      • Cheap
      • Ubiquitous
      • News systems
    • Cons
      • Low spatial resolution
      • Cloud cover
      • Thermal blocked
      • Actionability during the season is limited
    • Uses
      • Once canopy closes, management zones, yield prediction on large scale
  2. Drone
    • Pros
      • Prices have plummeted
      • Getting easier to use
      • Can achieve high-res from flying right above the canopy
      • Fly on demand
    • Cons
      • Someone has to fly
      • Battery limitations, Line of sight flight a requirement
      • Licensing required/still a bit complex
      • Make sure camera is good
  1. Manned Aircraft
    • Pros
      • Can cover large acres
      • Supports expanded range of sensors
      • Becoming more affordable
    • Cons
      • Flights are on a schedule with lag time
      • Compared to a drone, resolution is limited
      • Can be areas with no coverage

“With no analytics or application, data can be overwhelming.”

Agronomic Insights & Examples

  • Early season
    • Able to get insights in the field early
    • Pre-seasonal thermal
      • What areas of the field are dry and ready?
      • What areas of the field are wet and need time to dry out?
    • Tile Line Evaluation
      • You can see bare tile lines and how they affect the crop and its emergence.
      • This map can help justify if a portion of the field needs to be tiled.
    • Can help make and guide replant decisions
    • Weed detection
    • Tracking herbicide applications: misses and resistance
  • Mid-Season
    • Alert to N applicator error
    • Micronutrient deficiency in soybean
    • Japanese beetle feeding in field edges
    • Disease

Relating Aerial Imagery to Yield Impacting Factors

  • Control vs. compaction
    • Human error
  • Late Season
    • Sampling to estimate yield
    • Marketing decisions
    • Hybrid performance
    • Insight into hybrid performance with change
    • Lodging/greensnap
    • Harvest timing
  • Post Season
    • Anomaly over Time vs. Yield
    • Example post-season analysis

The Future

  • Measuring in-season crop performance is critical to making better decisions.
  • This is getting easier as collection methods and sensors are improving.
  • The result—more and more data that becomes impossible to keep up with.
  • It is easy to get caught up in data collection and analysis, but this information needs to be packaged in a way that saves farmers time and money.

General information  about Aeriel Imagery can be found here.

Share This Story