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Researchers Create App to Help Drones Improve Farm Efficiency

When Flown at the Right Times, Drones Can Help Farmers Adapt to a Changing Climate

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At right, a quadcopter drone hovers over orchard trees. On the left across a dirt road a man in a red shirt operates the drone.
Unmanned aerial vehicles, or drones, can help farmers monitor the state of fields and orchards but data can be affected by the position of the sun. A web application developed at the 嘿嘿视频 Digital Agriculture Lab helps farmers and researchers find the best time to fly for their date and location to avoid creating errors in data. (Digital Agriculture Lab)

Researchers at the University of California, Davis, have developed a web application to help farmers and industry workers use drones and other uncrewed aerial vehicles, or UAVs, to generate the best possible data. By helping farmers use resources more efficiently, this advancement could help them adapt to a world with a changing climate that needs to feed billions.

Associate Professor , director of the 嘿嘿视频 and postdoctoral researcher , who recently completed his doctorate in biological systems engineering under Pourreza, designed the app to make drones more proficient and accurate. Specifically, the platform helps drone users avoid glare-like areas called hotspots that can ruin collected data.

Drone users select the date they plan to fly, the type of camera they are using and their location either by selecting a point on a map or by entering coordinates. The app then indicates the best times of that specific day to collect crop data from a drone.

Jafarbiglu and Pourreza said that using this app for drone imaging and data collection is crucial to improve farming efficiency and mitigate agriculture鈥檚 carbon footprint. Receiving the best data 鈥 like what section of an orchard might need more nitrogen or less water, or what trees are being affected by disease 鈥 allows producers to allocate resources more efficiently and effectively.

鈥淚n conventional crop management, we manage the entire field uniformly assuming every single plant will produce a uniform amount of yield, and they require a uniform amount of input, which is not an accurate assumption,鈥 said Pourreza. 鈥淲e need to have an insight into our crops鈥 spatial variability to be able to identify and address issues timely and precisely, and drones are these amazing tools that are accessible to growers, but they need to know how to use them properly.鈥

Dispelling the solar noon belief

Diagram showing how sunlight can create false hotspots in drone data over orchards.
Depending on latitude and time of year, the sun can create false bright spots, or hotspots, in drone data.

In 2019, Jafarbiglu was working to extract data from aerial images of walnut and almond orchards and other specialty crops when he realized something was wrong with the data.

鈥淣o matter how accurately we calibrated all the data, we were still not getting good results,鈥 said Jafarbiglu. 鈥淚 took this to Alireza, and I said, 鈥業 feel there鈥檚 something extra in the data that we are not aware of and that we鈥檙e not compensating for.鈥 I decided to check it all.鈥

Jafarbiglu pored through the 100 terabytes of images collected over three years. He noticed that after the images had been calibrated, there were glaring bright white spots where they were supposed to look flat and uniform.

But it couldn鈥檛 be a glare because the sun was behind the drone taking the image. So Jafarbiglu reviewed literature going back to the 1980s in search of other examples of this phenomenon. Not only did he find mentions of it, but also that researchers had coined a term for it: hotspot.

Orchard trees seen from above. A red box surrounds the center of the image. The trees are brighter towards the top right corner.
Example of drone image data with hotspot.

A hotspot happens when the sun and UAV are lined up in such a way that the drone is between the viewable area of the camera鈥檚 lens system and the sun. The drone takes photos of the Earth, and the resulting images have a gradual increase in brightness toward a certain area. That bright point is the hotspot.

The hotspots are a problem, Jafarbiglu said, because when collecting UAV data in agriculture, where a high level of overlap is required, observed differences in the calibrated images need to come solely from plant differences.

For example, every plant may appear in 20 or more images, each from varying view angles. In some images, the plant might be close to the hotspot, while in others it may be situated further away, so the reflectance may vary based on the plant鈥檚 distance from the hotspot and spatial location in the frame, not based on any of the plant鈥檚 inherent properties. If all these images are combined into a mosaic and data are extracted, the reliability of the data would be compromised, rendering it useless.

Pourreza and Jafarbiglu found that the hotspots consistently occurred when drones were taking images at solar noon in mid-summer, which many believe is the best time to fly drones. It鈥檚 an obvious assumption: the sun is at its highest point above the Earth, variations in illumination are minimal, if not steady and fewer shadows are visible in the images. However, sometimes that works against the drone because the sun鈥檚 geometrical relationship to the Earth varies based on location and the time of year, increasing the chance of having a hotspot inside the image frame when the sun is higher in the sky.

鈥淚n high-latitude regions such as Canada, you don鈥檛 have any problem; you can fly anytime. But then in low-latitude regions such as California, you will have a little bit of a problem because of the sun angle,鈥 Pourreza said. 鈥淭hen as you get closer to the equator, the problem gets bigger and bigger. For example, the best time of flight in Northern California and Southern California will be different. Then you go to summer in Guatemala, and basically, from 10:30 a.m. to almost 2 p.m. you shouldn鈥檛 fly, depending on the field-oriented control of the camera. It鈥檚 exactly the opposite of the conventional belief, that everywhere we should fly at solar noon.鈥

Dotted line graph rising to a peak in the center with tails on each side.
Example of output from the app recommending times to fly in Canada.

Grow technology, nourish the planet

Drones are not the only tools that can make use of this discovery, which was funded by the . , an assistant professor of plant sciences at 嘿嘿视频, mainly uses towers to scan fields and collect plant reflectance data from various viewing angles. He contacted Jafarbiglu after reading his research, published in February in the , because he was seeing a similar issue in the remote sensing of plants and noted that it鈥檚 often ignored by end users.

鈥淭he work that Hamid and Ali have done will be beneficial to a wide range of researchers, both at the tower and the drone scale, and help them to interpret what they are actually seeing, whether it鈥檚 a change in vegetation or a change in just the angular impact of the signal,鈥 he said.

For Pourreza, the When2Fly app represents a major step forward in deploying technology to solve challenges in agriculture, including the ultimate conundrum: feeding a growing population with limited resources.

鈥淐alifornia is much more advanced than other states and other countries with technology, but still our agriculture in the Central Valley uses technologies from 30 to 40 years ago,鈥 said Pourreza. 鈥淢y research is focused on sensing, but there are other areas like 5G connectivity and cloud computing to automate the data collection and analytics process and make it real-time. All this data can help growers make informed decisions that can lead to an efficient food production system. When2Fly is an important element of that.鈥  

Media Resources

(ISPRS Journal of Photogrammetry and Remote Sensing)

Media Contacts:

  • Alireza Pourreza, Biological and Agricultural Engineering, apourreza@ucdavis.edu
  • Hamid Jafarbiglu, Biological and Agricultural Engineering, jafarbiglu@ucdavis.edu
  • Andy Fell, News and Media Relations, 530-304-8888, ahfell@ucdavis.edu

Jessica Heath is a content specialist in the 嘿嘿视频 College of Engineering. 

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