2015 Essential Guide to Precision Farming Tools
Unmanned aerial systems were featured in the Fall 2015 edition of Precision Farming Dealer.
All the unmanned aerial systems (UAS) used in the U.S. to date are small. While there are many uses for these aircraft in crop and livestock production, larger UAS will also be utilized in agriculture.
Smaller aircraft are ideal for scouting crops and livestock and can be used effectively to capture imagery that can be used for precision management decisions such as variable-rate, in-season fertilization, weed identification, livestock inventory and identifying sick animals. But small UAS are limited by flight time and cannot easily capture imagery of thousands of acres on the same day.
Large UAS will be needed to collect high spatial and temporal resolution imagery over entire regions in a timely manner. Most small UAS need to capture hundreds of individual images to make a single mosaiced image of one square mile — a large UAS could capture high resolution imagery of 1 square mile in a single image. This would make it possible to capture imagery usable for precision crop management over 100,000 acres in a single day.
The imagery would be processed into usable crop management information, stored in the cloud and made available for growers to download imagery for individual fields and a specific cost per acre.
Sensor technology for UAS is developing and changing quickly. Today, most agricultural users are utilizing color and infrared sensors. Both are very useful for field scouting, and the infrared can be effectively used to prepare vegetative indices of growing crops. Multispectral sensors will become more common on UAS because they can capture the red, green blue and infrared bands in a single flight.
There is still a great need for research to effectively use UAS in agriculture. Using remote sensing to identify and quantify crop nutrient deficiencies, disease symptoms and weed identification is not easy.
Most nutrient deficiencies and disease symptoms can be masked by other issues. For example, nitrogen and sulfur deficiencies and excess moisture can all cause chlorosis in corn plants. For now, imagery needs to be correlated to ground-truth data to have a high level of accuracy in field conditions.
In the coming year, North Dakota State University (NDSU) researchers will collaborate with selected crop producers to correlate the aerial imagery to detailed soil analyses and field observations, in-field optical sensor data and crop harvest yield data in selected fields.
The long-term economic impact to crop and livestock still needs to be determined. A primary objective of NDSU UAS work in 2016 will be comparing the utility and economics of the large and small UAS data collection systems for crop management. Commercial data management and analysis companies and agricultural producers and retailers will be able to use the comparison results to build future business models.
However, some issues that need further research and development include image transfer, processing and analyses. Transferring gigabytes of data over wireless or cellular networks is an obstacle now to UAS adoption.
Transfer will be improved by data compression techniques and selection methods that strip out just the image data needed for a specific application, and only transfer that needed portion of the data, so I expect that the time required to process data can easily be reduced.
Ultimately, crop and livestock producers are really only interested in information derived from remote sensing imagery. Producers will be much more willing to pay for a map showing where their crops are deficient in nitrogen than they will for the actual imagery. Timeliness, accuracy and reliability will be the mark of successful UAS businesses.