Feasibility of Using Drones in Environmental Decision Making

Aaron CapeloutoGeorgia Institute of Technology

7/30/2015

Introduction

Unmanned Aerial Vehicles (UAVs) are being used in applications ranging from biology (species counts) to civil engineering (surveying and traffic monitoring).

This project is focused on configuring a drone and taking multi-spectral images while the drone is in flight.

Once the images have been processed, the NDVI (Normalized Difference Vegetation Index) can be found revealing information about vegetative health.

Important to understand the regulations and the designation the pilot may fall under (nature of the work being done).

Regulations

Hobbyist – Includes people who are solely flying the drones for fun. Never take your eyes off the drone, avoid manned aircraft, and maintain ceiling height of 400 feet.

Commercial – Overall murky and poorly defined. Must obtain a COA (Certificate of Waiver or Authorization) or a Special Air Worthiness Certificate and have a valid pilot’s license. Process varies in length but can take up to a year.

Governmental – COA must be granted and a “declaratory” letter sent by the state attorney’s office to the FAA to even be considered. Provide for at least six months in buffer time.

What is NDVI?

Equation that reveals vegetation health in a given area.

Healthy vegetation does an excellent job at reflecting light in the Near-infrared range (NIR larger wavelengths and smaller frequencies than visible light).

Ranges from -1 to +1.

Deep water has values close to -1, 0 in barren areas (desert landscapes), and close to 1 in rainforests.

Live plants use visible light for photosynthesis, whereas NIR energy is too weak so it must be reflected.

Figure 1. Light reflected by three types of leaves.

Objectives

Assess the feasibility of using UAV’s in multispectral image capture used for transportation environmental decision making.

Configure and outfit aerial drone with multispectral camera.

Be able to process picture and figure out coordinate location using correction software.

Be able to draw conclusions on the health of the vegetation being photographed by analyzing the NDVI of each image.

Preprocess imagery to be used in a wetlands identification model.

Become familiar with the camera and uploading the images from the camera to the computer.

Equipment

X8+

Cheerson CX-20

Tetracam ADC Lite

FS-TH9X (Remote Controller) & LiveView™

Tarot Gimbal and GoPro™

Figure 2. X8+ and accessories.

Figure 3. Cheerson CX-20.

Methods (I)

Understanding the different parts of the drone before flying is an essential step for success and safety.

Multiple test photographs were taken using

the Tetracam ADC Lite. A Compact Flash card

reader is needed to upload images.

Figure 5. Test flight at the Lawn.

Figure 4. Image taken of inside classroom.

Methods (II)

Before flying under the designation of government researchers a COA is required. Our team is not in possession of one so we had to look elsewhere.

Fortunately Dr. Wekker and his graduate student Nathan Rose in the Environmental Science department have a COA and were willing to assist us.

Attaching the camera to the Cheerson CX-20 proved to not be as difficult as hoped. We used Velcro and zip-ties to secure the Tetracam.

Nathan flew the Cheerson CX-20 in standard mode and I served as

the spotter.

Flight location was on the property of Innisbrook Assisted Living in

Crozet.

Figure 6. Tetracam ADC Lite attached to the drone.

Flight Path

Figure 7. Screenshot of flight path using Mission Planner software.

Results (I)

Figure 8. These two images represent a color-processed image of the courtyard on the left with the NDVI of the same image on the right. The NDVI was close to 0.6 indicating healthy vegetation.

Results (II)

Figure 9. Aerial photos taken at Innisbrook. Color-processed image on the left. NDVI image in the middle in monochrome and on the right in color. The NDVI for this image was 0.8 indicating a healthy southeastern forest.

Conclusions & Recommendations

The flight went well and the camera remained securely fastened.

Obstacles encountered encompassed getting a handle on the regulatory requirements, challenges associated with attaching many items to the bottom of the drone, and finding a professor with a working COA.

Future recommendations for advancing this project include: Give plenty of time in advance to obtain a COA, at least 4-6 months.

Outline specific objectives for the flight well before it is time to fly, this way selecting proper equipment and location will become much clearer.

Strengthen relationships with other departments who are working on similar projects.

Consider purchasing a drone with longer battery life and increased wind resistance.

Use Mission Planner to pre-program flight path.

Acknowledgements

I would like to thank the MATS UTC program for providing me with this opportunity this summer. Thank you to Dr. Parkany, Dr. Culver, Dr. Goodall, and Ben Felton for their support and valuable advice. A special thanks goes to Dr. Wekker and his graduate student Nathan Rose for helping us fly the drone and providing us with a suitable location to fly!

References

Ramos, Jennifer. "Normalized Difference Vegetation Index." The Notable Trees of Villanova University. N.p., n.d. Web. 26 June 2015. <http://www47.homepage.villanova.edu/guillaume.turcotte/studentprojects/arboretum/NDVI.htm>.

"Tetracam ADC - Frequently Asked Questions." Tetracam. N.p., n.d. Web. 24 June 2015. <http://www.tetracam.com/pdf/ADC/ADC%20FAQ.pdf>.

"Public Operations (Governmental)." Federal Aviation Administration. N.p., 10 Feb. 2015. Web. 24 June 2015. <https://www.faa.gov/uas/public_operations/>.

PixelWrench2. Vers. 1.5. Chatsworth: Tetracam, 2015. CD-ROM.

Meyers, Jessica. "Researchers Decry Limits on Drones." The Boston Globe 18 Aug. 2014: n. pag. Print.

Questions?