DroneDeploy has released new capabilities to help farmers perform more accurate plant health analysis and process high-quality maps during every stage of crop growth. Farmers can now create field maps using sensors designed for agriculture, including Sentera’s near-infrared and SLANTRANGE’s calibrated multi-spectral sensors.
“We’ve listened to our customers’ feedback and requests and worked with leading technology partners in the industry to help growers detect crop variability sooner and compare plant health over time,” says Mike Winn, DroneDeploy CEO and cofounder.
The company has also released improvements to its proprietary map-processing algorithms – a timely addition that can address some of the most common challenges farmers face when mapping late-stage crops.
“Until now, stitching late-stage crops has remained an unsolved problem in image processing,” says Nick Pilkington, CTO and cofounder of DroneDeploy. “We’re excited to deliver a solution to our customers that lets them create high-quality maps at all stages of crop growth.”
Giving Farmers More Choices
It’s no secret farmers have a number of hardware options when it comes to selecting a drone to evaluate crops. By partnering with SLANTRANGE and Sentera, DroneDeploy customers will now have more freedom to use the camera or sensor of their choice. While most growers begin with visible-spectrum cameras that come standard on drones like the DJI Phantom 4 Pro, many turn to sensors designed specifically for ag to perform more accurate, scientific analysis of plant health.
Using near-infrared sensors from Sentera and calibrated multispectral sensors from SLANTRANGE, which are all compatible with the latest DJI drones, allows DroneDeploy customers to fly and capture imagery and process interpret maps. To create a map with these sensors, users install the free SLANTRANGE or Sentera application within DroneDeploy, fly using the DroneDeploy mobile app, and upload imagery to DroneDeploy for processing. Once the map is complete, users can view, analyze, and share plant health data specific to the sensor used.
The near-infrared sensors from Sentera, now compatible with the DroneDeploy workflow including the High-Precision NDVI Single sensor and the Sentera Double 4K, allow growers to create NDVI (normalized difference vegetation index) maps to accurately detect crop stress.
“Sentera is excited to bring our most popular and most affordable high-precision NDVI sensor to the DroneDeploy platform. We’re committed to supporting our customers' preferred workflows and enabling an open and accessible set of downstream analytics based on genuine NDVI and other index products,” says Eric Taipale, Sentera's CEO. “Our partnership with DroneDeploy does just that, providing DroneDeploy users a seamless integration with Sentera’s high-quality index and multispectral sensors going forward.”
The SLANTRANGE 3p sensor captures high-resolution, calibrated, multispectral imagery data using patented sunlight calibration algorithms so farmers and agronomists can accurately compare crop data over time.
“SLANTRANGE is committed to promoting an open ecosystem that allows customers to collect and process their data using a combination of tools that work best for their business,” says Matthew Barre, director of strategic development at SLANTRANGE. “This partnership gives DroneDeploy customers access to the accuracy and specificity of SLANTRANGE's true multispectral imagery.”
Reducing Holes in Maps
Late-stage crops pose a challenge for mapping software, which relies upon identifying unique points that appear in several different images to stitch together a map. In 10-foot-tall corn, it can be very difficult to spot unique points from image to image. Farmers who have used drones for mapping in the past are all too familiar with what can result: maps with holes, warped areas, or even maps that fail to process at all. Fortunately, after analyzing data from over 10 million acres mapped and hearing feedback from hundreds of users, DroneDeploy has made significant improvements to a proprietary processing algorithm to address the specific challenges of late-stage field maps. Extensive testing demonstrated that incomplete maps processed using the previous stitching algorithm resulted in complete maps 90% to 95% of the time when reprocessed using the improved algorithm.
One of the reprocessed maps (pictured) belonged to Kevin Wright, a corn and soybean grower and commercial drone pilot in Illinois.
“Being able to close a hole as big as that,” he says, referring to the difference between his original map and the reprocessed complete map, “is very impressive, especially for a map flown in windy conditions. It just proves that DroneDeploy is headed in the right direction as far as being able to solve these particular problems.”
Not only were the reprocessed maps complete, many of them also showed significant improvements in accuracy and image sharpness.
Another improvement DroneDeploy has made includes Fieldscanner, which offers real-time, offline field mapping.
To learn more about how to use drone mapping to monitor plant health, check out DroneDeploy’s Guide to Crop Scouting with Drones. To learn more about different drone and camera options for agriculture, read DroneDeploy’s Drone Buyer’s Guide.