What Farmers Need to Know?
Whole field, in-season, current condition data is one of the most valuable pieces of information in a precision program. With this data a farmer can spot problems early and rapidly select appropriate interventions.
Manned surveillance flights and satellites using near infrared cameras (also called NDVI cameras) and RGB cameras are the incumbent data sources for whole field condition assessment, but they aren’t one-size-fits-all solutions. These sources are best suited for surveying tens of thousands of acres at a time, where the time and resources required to schedule and scout by these means justifies the expense and complexity.
Agricultural drones represent a new way to collect field-level data. The most compelling reason for using drones is that the results are on-demand; whenever and wherever needed, the drone can be easily and quickly deployed. A grower or service provider can have a drone in the back of the truck and get actionable, field-level information the next day or sooner. It’s hard to beat the immediacy and convenience of planning the mission, collecting the data, and getting near real-time results; only drones offer these benefits.
Drones are affordable, requiring a very modest capital investment when compared to most farm equipment. They can pay for themselves and start saving money within a single growing season. Operation is relatively simple, and getting easier with every new generation of flight hardware. They’re safe and reliable. They are easy to integrate into the regular crop-scouting workflow; while visiting a field to check for pests or other ground issues, the drone can be deployed to collect aerial data. Yet, the real advantages of drones are not about the hardware; the value is in the convenience, quality and utility of the final data product.
Drone-enabled scouting is a convenient way to collect the “what is happening right now” data layer. There are three main elements to using a drone effectively to do this: getting the sensors above the field, the sensors themselves, the data analysis. Finally, there are the regulatory and business aspects to consider.