As you have seen throughout this report, aerial imagery has been a “thing” in agriculture for decades. Systems and delivery mechanisms have come, gone, and evolved. New satellite deployment for image capture has exploded in recent years, while the resolution and “on-demand” capability of drone systems have grabbed much of the current spotlight. Finally, there has been an earnest re-focus on imagery collected via manned airplane, access to a wide range of imagery has never been easier and with more options.
Still, value creation using imagery on the farm has continued to be elusive, in large part because so much of what row crop farmers and technology integrators hear from imagery vendors is about what they believe farmers want from their imagery. We hear much less from row crop farmers and their agronomists about what is actually working, and what they need more of from imagery as a layer in the farm decision-making process.
Back in April, I engaged in a Twitter conversation among some top-shelf farmers and
integrators: Steve Pitstick, a northern Illinois farmer; Cory Willness, a Saskatchewan-based agronomist; Jeremy Wolf, an Illinois-based equipment and technology dealer, and Isaac Ferrie, an Illinois crop consultant.
These experts in row crop farming discussed when, how and what type of imagery can help to make actionable decisions in row crops. They asserted that imagery alone does not provide the answer. We need other field data such as weather, soil composition and moisture, field drainage, fertility; machine as-planted data, as-applied nutrients, and ultimately how to make decisions that trade off reducing cost or increasing yield and revenue.
For all the frustration and confusion about the value of imagery, interest remains remarkably high. An informal poll of our Prassack Twitter followers this past March asked the question, and people are interested — more than 1,000 responded!
Good Examples Abound
So, the table is set: We have a vast array of imagery solutions embedded in ag retailer and co-operative agronomy programs, and strong general farmer interest. But farmers want to know how to take it to the next logical step. “I have this ‘pretty picture’ of my field, but how do I turn it into an actionable piece of collected data that improves the efficiency and/or profitability of my farm?”
As we talk to many farmers and technology integrators in our work, we have been trying to extract some clues about imagery value. We also have researched use cases and return-on-investment studies for industries such as input research, insurance, banks as well as other crop types orchards, vineyards, vegetables, berries, greenhouses, animal management, etc. These are useful as we consider the benefits of imagery in row crops.
When looking at the application of technology to help farmers with decisions, start with the farm operation cycle, which can be defined this way: Planning – Planting – Managing – Spraying – Irrigation – Harvest. With this as a guide, below are seven examples of benefits from imagery use and its partner technologies that combine to deliver actionable value to growers.
1. Plan Variable Rate Prescription Using 5-Meter Satellite Imagery and Near Infrared NDVI processed imagery taken from peak growing periods over 15 years. Topographic imagery and soil composition assist agronomists and their farmers to identify zones for variable rate prescriptions. The images demonstrate plant vigor and stress areas within the field attributable to weather, seed or fertility. Benefit: South Dakota Wheat Growers in Aberdeen, SD, create variable rate prescriptions through 5 meter satellite imagery from Geosys and their proprietary MZB Software solution. Grower customers realize a benefit of 23% better yield at 5% additional input cost.
2. Planting Timing Based on 20-Centimeter Aerial Thermal Imagery. Thermal imagery can help to determine “when is the soil warm enough” to plant temperature sensitive crops like cotton. Benefit: Cotton farmers in Georgia use TerrAvion 9 centimeter thermal imagery to identify fields that are warm enough to plant cotton. The results are that the grower can ensure cotton seeds are planted at the right time, incur less loss from cold or delayed growing system while ensuring faster time to gin.
3. Pivot Irrigation Using 10-Centimeter Aerial Imagery. Nebraska Farmer and Irrigation Technology Specialist Roric Paulmann runs 80 pivots with only 4 inches of available water per year. Imagery indicates the optimal time to apply irrigation for best yield. Benefit: Using AirScout Thermal imagery with the Arable rain sensor on his pivots, Roric sees a cost savings of $20,000 per pivot.
4. Fungicide Application at Less Than 50-Centimeter Aerial Imagery. Sclerotinia disease risk in canola is based on crop density. Terry Aberhart, a farmer and crop consultant in Saskatchewan, was able to use imagery at this resolution to determine timing and variable rate fungicide application for his canola. Benefit: Improved $50 per acre net profit.
5. Crop Insurance. Using satellite imagery from RapidEye and aerial imagery from Marvx provides an accurate and timely damage assessment, leading to expedited payment of a claim. Insurance companies also benefit through optimization of their field adjustors’ schedules, and better customer satisfaction. Benefit: Faster and more complete payment on claims.
6. Imagery as a Problem Solver. Imagery is also being used to identify problems we did not know we had. For example, during one season, regional precision ag specialist Blain Hope at CHS in Idaho noted a yellow circle in the crop imagery with potato field pivots, indicating a nozzle issue that could be checked out and addressed by a field scout. Benefit: There’s a need for “smart nozzles” that can recognize a problem and communicate that they need to be replaced or fixed.
7. Layers of Data for Field Management. From farm management systems like Climate FieldView, we are able to go beyond just imagery. By combining elevation, zone maps, NDVI image, soil and yield maps — we are able to build better field prescriptions. Benefit: by visualizing the field data we can optimize input selection and costs by production areas of the field.
The bottom line is, imagery is a tool in the toolbox, and as such it is not designed to fix every problem faced on the farm. To maximize its usefulness, imagery must complement the many other resources farmers have at their disposal: soil type data, inputs, weather data, machine data, agronomic knowledge and many others. As an industry, we need to collaborate to leverage our combined learning from all of these data sets. We need to apply this data at different times based on our understanding of the farming process. And ultimately, we need to stop providing raw data and start providing information that helps farmers make the next decision.