Case Study: Using Drones Equipped with Industrial Cameras to Monitor Crop Health

The agricultural sector always endeavors to produce better and healthier plants and tries to cut down the negative effect on the environment. Using fewer fertilizers and pesticides, saving water, and boosting yields are the three main focuses of this industry.

AggieAir is a member of the Utah State University’s Water Research Laboratory. In 2006, AggieAir’s founders planned to do this by deploying a remote sensor system to track the moisture content of soil. Dr. Mac McKee, the Lab director, strived to achieve this with unmanned aerial vehicles (UAVs), but he also specified that the aircraft should be easy to use, cost-effective, and the imagery obtained from the aircraft should be processed easily. Keeping these things in mind, a user-friendly and cost-effective UAV system was developed to track the vegetation health from the air.

Solution: UAV System to Monitor Vegetation Health from the Sky

Utilizing consumer-grade cameras the original system worked relatively well and was much more economical, opposed to utilizing manned aircrafts. It also remained unaffected by cloud cover and was able to accomplish superior resolution over the satellites in orbit. The system exceeded labor intensive techniques, like blimp-based photography that covers roughly 1 km of ground in half a day, with the initial model spanning 25 km in the morning.

About the System

The operation of the system involves measuring the resolution needed for the application, which governs the height that the aircraft should fly at to capture the data accurately. After determining the altitude, one or more flight paths are set based on the preferred coverage area. This is followed by uploading the flight path to the onboard flight computer of the UAV. Table 1 shows data related to flight altitude, swath width, and ground resolution.

Table 1. Swath width and ground resolution acquired at different altitudes from different cameras

Flight Altitude (Above Ground) Swath Width Ground Resolution
Lt965R Lt1265R Lt965R Lt1265R
20 0m 156 m 164 m 5c m 4 cm
500 m 390 m 411 m 12 cm 10 cm
1000 m 780 m 82 2m 23 cm 19 cm

Benefits of Lumenera’s Lt965R

Lumenera’s Lt965R cameras offer the following benefits:

  • No anti-aliasing filter leads to higher and sharper resolution images
  • Extremely light weight cameras with robust aluminum body weighing just 175 g each
  • GPIO hardware trigger ability minimizes triggering delay to microseconds
  • High bit depth of 14 bits/pixel
  • 20 cm of resolution at a height of 1 km above the ground
  • A dynamic range of 65 dB

AggieAir Requires Technology Beyond what Point and Shoot Can Offer

Due to varied applications and their associated complexities, there is a huge demand for better quality imaging. The point and shoot style cameras used by AggieAir are bulky, too complicated to interface with, and do not provide repeatable results. In addition, many off the shelf, point and shoot cameras employ anti-aliasing filters that tend to minimize the sensor’s effective pixel count.

Given that high-frequency patterns do not exist in nature, AggieAir looked for a suitable solution that not only helped to remove the anti-aliasing filter from the equation, but also assisted in addressing the concerns regarding a compact and better quality device. AggieAir were also searching for a way to simplify the interface between the plane and the camera, and to enhance their triggering mechanism to obtain better accuracy between each image interval.

Industrial-Grade Lt965R Cameras Replace Consumer-Level Point and Shoot

Two lightweight 9 megapixel Lt965R USB 3.0 cameras were used to substitute AggieAir’s original consumer-level, point and shoot camera. Lumenera supplies monochrome as well as color versions; the monochrome model was used to photograph near infrared and the red edge of the scene, while the color version is used to capture the color spectrum (Figures 1 and 2).

Aerial view of a vineyard surveyed. Image captured with Lumenera’s Lt965RM (monochrome).

Figure 1. Aerial view of a vineyard surveyed. Image captured with Lumenera’s Lt965RM (monochrome).

Aerial view of a vineyard surveyed. Image captured with Lumenera Lt965RC (color).

Figure 2. Aerial view of a vineyard surveyed. Image captured with Lumenera Lt965RC (color).

The broad spectrum and highly precise data enabled the team to accurately calculate the normalized difference vegetation index (NDVI), which measures the vegetation health by determining the varied wavelengths of light that are reflected and absorbed by the soil and plants.

A higher resolution with less pixels was achieved, as the team switched to the 9 megapixel Lt965R from a 10 MP point and shoot camera. The former eliminates the need for an anti-aliasing filter that is often used in UAV applications. Now, raw data is capered by each pixel, rather than assigning a subset of pixels to carry out the redundant filtering operations. When the filter is removed, sharper images are obtained, and blurring does not pose a problem.

The Lt1265R was integrated to AggieAir’s range of sensors to provide even more resolution, at 12 megapixels. The Lt1265R and Lt965R cameras provide 14 bits of data for each pixel, with a dynamic range of 59 dB and 65 dB, respectively and the same is output in an unchanged raw format to improve the usable data. This leads to improved data quality for further analysis by AggieAir’s post processing software.

The transition from an off-the-shelf, consumer-grade point and shoot camera to a rugged and industrial-grade camera provided innovate functionalities and features that are only seen in commercial-grade instruments. The cameras’ general purpose input-output (GPIO) port was used to minimize the triggering delay from a single second to the order of microseconds. This not only enabled AggieAir to control and trigger both cameras, but also allowed it to ensure an almost seamless image overlay of the monochrome and color frames. Figure 3 displays the cameras, and Figure 4 shows how the white balance is carried out in the field.

View of cameras in payload

Figure 3. View of cameras in payload

Performing white balance in the field

Figure 4. Performing white balance in the field

In addition to supplying Lt1265R and Lt965R cameras, Lumenera provided AggieAir with Linux API and SDK with technical assistance to integrate the current Linux operating system on board the aircraft.

Conclusion

In addition to other improvements, the upgraded camera solution enabled AggieAir to expand from the agriculture field to other critical areas of UAV imaging and analysis. Advancements have been made in the civil industry to evaluate bridges and roads in Riparian Studies like hydraulic modeling, in emergency response operations, where flooded land can be imaged and mapped quickly, and in Wetlands Management to deal with persistent agricultural species.

This information has been sourced, reviewed and adapted from materials provided by Lumenera Corporation.

For more information on this source, please visit Lumenera Corporation.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Teledyne Lumenera. (2019, August 21). Case Study: Using Drones Equipped with Industrial Cameras to Monitor Crop Health. AZoOptics. Retrieved on September 19, 2019 from https://www.azooptics.com/Article.aspx?ArticleID=1099.

  • MLA

    Teledyne Lumenera. "Case Study: Using Drones Equipped with Industrial Cameras to Monitor Crop Health". AZoOptics. 19 September 2019. <https://www.azooptics.com/Article.aspx?ArticleID=1099>.

  • Chicago

    Teledyne Lumenera. "Case Study: Using Drones Equipped with Industrial Cameras to Monitor Crop Health". AZoOptics. https://www.azooptics.com/Article.aspx?ArticleID=1099. (accessed September 19, 2019).

  • Harvard

    Teledyne Lumenera. 2019. Case Study: Using Drones Equipped with Industrial Cameras to Monitor Crop Health. AZoOptics, viewed 19 September 2019, https://www.azooptics.com/Article.aspx?ArticleID=1099.

Ask A Question

Do you have a question you'd like to ask regarding this article?

Leave your feedback
Submit