Converting a Skeptic with One Field Map
A first time mapper in agriculture shares what he learned about his crop
One thing we pride ourselves on here at DroneDeploy is how easy it to use our software to get real insights that help your business. But what does that really mean? Just how easily and quickly can someone start getting real value from DroneDeploy?
A few weeks ago, we saw this tweet from a brand new user.
Intrigued, we reached out. Brent told us the story of his very first flight with DroneDeploy and how he used the map he made to make a decision on his farm and to make a surprising discovery.
Brent grew up in rural Missouri on the family farm and continues to be actively involved in its operations. Several years ago, Brent had an internship with a local commercial spraying company. Towards the end of the summer when the crops matured, they would spray the crops with an airplane crop duster. “One day I was at the airport helping the crop dusters and I jokingly asked them for a ride. They took me up, and I instantly got hooked on seeing fields from the sky,” said Brent.
Later that summer, after doing a bit of research, Brent purchased a Phantom 2 vision and fell in love. Since then, he’s upgraded to a Phantom 4 and gotten into drone cinematography. He follows a number of drone advocates online, and one of them recommended DroneDeploy. Brent decided to sign up for the free trial and put DroneDeploy to the test by flying a field on the farm.
Putting DroneDeploy to the Test
For his first map, Brent chose a 40 acre field with wheat on the top (northern) portion, and rye in the lower (southern half). “We had a pretty decent storm come through, and my dad told me it had flattened the grass on the lower half of the field,” said Brent.
“I thought it would be a good field to fly to see if I could see the variation between the two crops and to see the damage from the wind.”
Brent used his Phantom 4 and the DroneDeploy app to fly and map the field.
“I didn’t know what to expect, but everything went smoothly. Dragging the perimeter around, clicking go, everything worked the way it was supposed to,” said Brent.
The whole flight took only 15 minutes. Once the drone landed, Brent uploaded the imagery to DroneDeploy and a few hours later, had a map of the field.
Evaluating the Weather Damage
The first thing Brent did with his completed map was look at the southern portion of the field to inspect the wind damage. “We knew there would be an issue in this field and could see it from the road, but the map allowed us to see the extent of the damage,” said Brent.
Using the information, Brent and his Dad could make a better decision about how to harvest the Rye as hay. “This allowed us to adjust our mower so that it would be more suited for blown-down grass.”
Brent was also pleased that he could clearly see the difference between the two fields from his map. The map had demonstrated its ability to show both the wind damage and the variation between the two fields — but what was to come would be even more exciting.
A Surprising Discovery
A few days later, when Brent was helping his Dad harvest the rye field, he noticed something odd at the edge of the wheat field to the north. Some of the plants had reddish-yellow fungus growing on them. This fungus — rust — can significantly decrease yields on crops like wheat.
Brent wondered, would the crop stress from the rust be visible on his map? Brent pulled his phone out of his pocket and opened up the map to look at the place where he had found the rust. It was difficult to see a difference in the orthomosaic (photorealistic) map, but when he clicked the “Plant Health” button, it was a different story.
“When I pulled up the map, sure enough, where I was standing was a very visible red spot on the map”, said Brent.
The areas of red coloration also easily enabled Brent to see the extent of the rust in the field.
A Vegetation Index for a Regular Camera
How was the map able to identify the unhealthy area? The “Plant Health” tools in DroneDeploy allow users to apply vegetation indices, like NDVI, to their maps. These indices help highlight differences in coloration that may be difficult to see from the original imagery, by coloring the entire map in one of three colors (red, yellow, green) based upon how the index categorizes the health of particular areas.
NDVI (normalized difference vegetation index) is perhaps the most commonly-used vegetation index, but it is intended to help interpret imagery from near-infrared cameras. Since Brent’s Phantom 4 camera captures visible spectrum, or RGB (red, green, blue) imagery, the NDVI index isn’t appropriate. However, the default index used in the “Plant Health” section of DroneDeploy, VARI (visible atmospheric resistant index), is intended specifically for visible spectrum or RGB imagery, and classifies areas of the map based upon the amount of “greenness” detected.
To Treat or Not to Treat?
So what can a grower do with the knowledge of the rust infection? “This type of data from DroneDeploy can help a grower estimate his potential yield,” said Brent.
“At the beginning of a growing season, the farmer will set a yield goal. He can then adjust his input cost accordingly. These results allow the farmer to adjust his decisions to either maintain or adjust his yield goal. Knowing that X number of acres are infected with this fungus, he can expect a 20% decrease in his yield goal for X number of acres which will result in Y dollar loss. If the price of the crop is high enough, and the cost to treat the infected area is low enough, then the farmer has the opportunity to treat the red areas of the map to increase the yield.”
In this case, given that the wheat was planted as a cover crop and for generating seed and hay, Brent and his dad decided it wouldn’t be cost effective to treat the rust. “But this map gives us an idea what to expect come harvest time so that we won’t be caught off guard”, said Brent.
Although initially skeptical, Brent is now very excited about the future of drone mapping in agriculture. For now, he’s working on his flying, experimenting to find the best combinations of heights and overlap for making maps of different types of crops for different purposes. He’s also intrigued by the possibility of using drone map shapefile exports to generate variable rate prescriptions for nitrogen, pesticides and other applications.
“My favorite thing about DroneDeploy”, said Brent, “is the usability of the maps — you can pinch and pull to zoom, and easily make measurements.”
Where to Learn More
Want to learn more about how you can use drone mapping on your farm? Check out our help center to learn more about the practices and tools mentioned in the case study, including:
- Using vegetation indices to detect crop stress
- Using plant health data to define zones and grids
- Sharing and exporting your data
Try DroneDeploy for Agriculture
You won’t believe how easy it is to get started with DroneDeploy. Sign up for your free trial or learn about our Seasonal Ag Package (available for signup until June 30, 2016), which includes all of the ag-specific mapping capabilities you need, as well as training and support to help you make the most of it.