Multirotor Drone Applications in Rappahannock County, Virginia
Final Project Report by Thomas A. Woolman

ES555 - Small Format Aerial Photography, Emporia State University, Fall 2014 Semester


·ES555 Course Syllabus

Web page last updated:
24 NOV 2014

Small format aerial photography (SFAP) is a methodology to rapidly and inexpensively obtain adaptable and easily applicable high resolution images of man-made and natural ground features. Technologies employed for SFAP could include various kite systems, blimps, manned and unmanned aircraft platforms. The unmanned multirotor aircraft platforms are now more commonly referred to as drones. All of these flight systems may carry camera systems aloft, most commonly digital cameras with both video and still image capabilities and auto-focusing systems. These camera systems are typically separately controllable from the flight system, allowing pan and tilt management of the camera independent of the pitch and heading of the UAV.

Images and video are typically downloaded from the cameras after landing, however in the case of some of the more advanced camera systems typically coupled with Wi-Fi signal capabilities, images may be previewed at a lower resolution in real-time via Wi-Fi enabled devices running software applications. These applications typically run on Droid or Apple iPad/iPhone devices to allow adjustment of camera pan and tilt and video or still image mode, as well as display aircraft telemetry data including UTM coordinates, altitude, compass heading, and remaining battery charge.

The ES555 course at Emporia State University held multiple SFAP field trips in the fall of 2014 to allow on-campus students to utilize multiple aerial photography systems. The author is a distance learning graduate student and therefore elected to obtain a multirotor UAV and utilize it in his home area in central Virginia along the eastern boundary of the Blue Ridge anticlinorium. The objective of this study was to obtain useful SFAP images for the course. The UAV purchased was a DJI Phantom 2 Vision+ model, a quadcopter drone with an onboard flight computer, GPS navigation, altimeter and gyroscope sensors and a gimbal mounted pan and tilt digital camera system and a Wi-Fi camera control/image preview/first-person video flight control system.

This final project report starts with an analysis of techniques utilized to operate and manage the quadcopter UAV and camera system, obtain images and how they were processed after the flights. A review then follows of the advantages and disadvantages of quadcopter UAV SFAP that were observed during these exercises.

Multirotor UAV Methods

Multirotor drone systems typically have two general flight control modes: first person operations (semi-autonomous) control or fully-autonomous control. The difference between the two is that semi-autonomous flights are conducted without pre-programming the drone with specific flight and camera mission instructions, and the drone flight operations are managed by the human pilot at all times. Fully-autonomous control involves the use of the on board GPS and altimeter system and programmable on-board computer system to fly to specific waypoints at various altitudes, conduct camera still image or video operations, and land at a pre-defined UTM coordinate. In the case of this study, all drone flight operations were conducted in the semi-autonomous mode. Why first person flight operations are referred to as semi-autonomous flights is explained further below.

Multirotor UAVs (Hanford, et al., 2005) are stated as having advantages compared to a more traditional manually piloted remotely controlled helicopter platform. Some of these advantages include the use of a quad rotor system (many larger, professional grade UAVs now include six or more multirotor systems for increased lift and maneuverability). The quad (or more) multirotor system requires no cyclic or collective pitch adjustment by the human pilot, as those flight dynamics are controlled by the onboard computer making minute adjustments to individual multirotor engines with thousands of calculations per second, with the aid of a suite of sensors and complex software without any human intervention.

Other advantages include simpler control mechanisms because of the on-board computer system that controls the multi-rotor engines in real time, to counteract wind and thermal layer atmospheric turbulence without the need for human intervention. In a real sense, the multirotor drones are actually flown by computer software, even during first-person controlled operations, making them truly semi-autonomous even during direct flight operation.

DJI Phantom Flight Controller, image compliments of DJI.

The human pilot via the "flight controller" wireless remote control sends a signal to the drone to control all of the flight characteristics including yaw, throttle, pitch and roll. However the drone's on board software then interprets those signals and controls the UAV's engines with calculated instructions in order to execute the maneuver commands. A perfect example of the advantage of this dynamic is in a low altitude hover maneuver, something that traditionally requires a high degree of skill by the pilot of a traditional helicopter (either full size or remotely controlled). Because of flowing air currents surrounding the helicopter, the pilot must make constant manual adjustments to the aircraft throttle, cyclic and collective pitch of the rotary wing blades in order to maintain the hover.

With the multirotor UAV, hovering is simply a matter of increasing the throttle to instruct the drone to obtain a desired altitude, and once that altitude is obtained the human pilot no longer has to manipulate the flight controls because now the on board computer will maintain position and altitude using on board sensors including an altimeter, electronic compass, GPS receiver and gyroscopes until instructed to perform a new maneuver. The advantage of such a platform for SFAP can be significant, because it now allows the operator to focus on the separate digital Wi-Fi camera computer controls to manage tilt, pan and camera light sensitivity as well as manage video or still image modes, all with just a single person. The Wi-Fi computer camera system of the DJI Phantom 2 Vision+ also allows for real time lower-resolution viewing of everything being seen by the camera, even without taking an image or video.

This allows the pilot to not only select a good image before taking a picture, it also allows for maneuvering the drone to an optimal location and altitude to best meet the mission objective. This almost entirely removes the guesswork out of where to fly the drone and how to arrange the camera system to obtain the best possible images and provides the operator with a huge time efficiency advantage.

DJI Phantom Wi-Fi flight telemetry and camera control smartphone/tablet application and "first person view" streaming video feed, image compliments of

The weakness of the semi-autonomous flight control system is that the multirotor UAVs have a distinct flight performance window. That is to say that the ability of the on-board computer to manage the engine systems and execute flight instructions is limited by environmental factors, primarily wind. In the case of the DJI Phantom 2 Vision+, it is extremely inadvisable to conduct flight operations in wind speed conditions exceeding approximately 25 miles per hour. This is because the thrust provided by the multirotor system could be overwhelmed by high wind gusts, resulting in loss of aerodynamic control and a high likelihood of a catastrophic crash.

When such a crash condition begins to occur, the pilot is virtually helpless as the on-board computer will be attempting to compensate for wind conditions it cannot match, and new flight instructions will have no effect while the computer fights in vain to regain control. An additional weakness of the semi-autonomous flight control system is the range of both the flight control radio transmitter, and more importantly the Wi-Fi flight telemetry and camera control system. The Phantom drone's wireless flight controller system has a direct line-of-sight range of approximately 800 meters.

This 800 m range extends in 3 dimensions from the drone to the operator. For example, the drone may have an altitude of only 200 meters but it could be 850 meters from the human operator on either the vertical or horizontal axis, which would most likely place the drone out of contact range with the operator. As previously mentioned, this drone also has a secondary wireless control system using a digital Wi-Fi signal. The Wi-Fi system does not control the aircraft, only the camera and gimbal system. However it does also provide the pilot with the real-time video camera view from the drone, as well as flight telemetry data (altitude, compass heading, and battery life remaining).

Wi-Fi is notoriously weak and would not ordinarily be able to extend to the 800 m distance of the flight control system, but the DJI Phantom series employs a Wi-Fi Extender, which boosts the range of the signal to approximately the same distance as the flight control signal. The two signals do not interfere as they are on widely different UHF frequency pairs. The wireless flight controller operates at 5.8 GHz and the Wi-Fi Extender system operates at 2.4 GHz.

The pilot uses a Droid or an Apple device to run the DJI application software, and then configures the phone or tablet to connect to the Wi-Fi Extender as its Wi-Fi "source". The Phantom drone likewise will automatically attempt to communicate with the Wi-Fi Extender that has a unique MAC and IP address that it has previously been configured exclusively to operate with (preventing a pilot with another DJI control system from taking control of the drone without prior authorization via re-configuration). The Wi-Fi Extender is normally attached next to the wireless flight controller along with a small clamp for attaching your Wi-Fi-enabled phone or tablet. This provides a handy control interface system that is manageable and self-contained for field operations. Understanding the UAV's flight performance window and the limitations of the flight control system ranges are key to successful drone operations.

Study Area

The study area was located near the author's residence on Battle Mountain in Rappahannock County, Virginia. The mountain is designated by the US Geological Survey as a late proterozoic felsic volcanic rock formation. It is the northernmost unit of the larger Robertson River Igneous Suite of central Virginia (USGS, 2003). Imaging operations were conducted in October 2014 as leaf color was starting to change. Images were acquired from the western slope area of Battle Mountain, in the early afternoon.

Images were taken of mountainside terrain from both high and low oblique angles and vertical images directly overhead from high altitude (approximately 150 meters). The rural terrain in this area is primarily forested (ash, red oak, poplar, cherry and maple trees predominate) or consists of cattle pasture and hay fields. Due to the heavily sloped nature of the terrain in the Blue Ridge anticlinorium, row crops are uncommon except for vineyards and orchards which prefer well drained soil and do not require annual plowing to maintain.

Obtaining Images

Image acquisition was started by preparing the UAV drone by charging the lithium polymer batteries. Each 2800 mAh capacity, 3-cell 11.1 volt battery provided approximately 30 minutes of flight time on a full charge, depending on altitude flown (throttle speed) and wind factors that the drone needed to exert energy to compensate against to maintain flight characteristics. Flights began by activating the drone and allowing it to acquire GPS satellites, which took approximately one minute. Seven satellites needed to be acquired to obtain maximum GPS flight accuracy for automated return. Automated landing return is an optional feature for use in case of an on-board problem or low battery cycle condition during semi-autonomous flights. GPS navigation during semi-autonomous flight was not a requirement if the pilot did not want an automatic return failsafe engaged. Fully autonomous (pre-programmed) flight operations rely entirely on GPS and magnetic compass navigation but that feature was not used in this study.

Upon confirmation of accurate GPS signal acquisition (indicated by the drone's flashing green LEDs), communication between my Google android smartphone and the drone Wi-Fi Extender was established using the smartphone Wi-Fi control menu. Once the link was established, the DJI Phantom flight software on my android phone was executed and I was able to observe flight telemetry data as well as a streaming camera video image on my phone.

The Battle Mountain Multirotor UAV Ground Crew conducting SFAP operations, October 2014. Note the smaller Wi-Fi Extender unit mounted on top of the larger wireless flight controller in the left image che.

The flight was then begun once the drone was securely sitting on level ground. The author then hovered the drone at an altitude of approximately 5 meters and performed various flight checks such as in-flight rotations and ascent and descent flight validation. Once confident that all controls were properly working the author then was able to begin climbing to the desired altitudes and begin obtaining SFAP images.

Western Slope of Battle Mountain

Western Slope 1

High oblique image acquired 17 October 2014. Western slope of Battle Mountain, facing northeast. Little Battle Mountain is visible to the north (left of) of the summit of Battle Mountain.

Western Slope 2

High oblique image acquired 17 October 2014. Western slope of Battle Mountain, facing north.

Western Slope 3

High oblique image acquired 17 October 2014. Western slope of Battle Mountain, facing north.

Western slope 4

High oblique image acquired 17 October 2014. Western slope of Battle Mountain, facing northwest.

Western slope 5

High oblique image acquired 17 October 2014. Western slope of Battle Mountain, facing southwest. Sun glint, the specular reflection of sunlight from the surface of the lake water, is distinctly visible.

Western slope 6

Image acquired 17 October 2014. Western slope of Battle Mountain, facing south. Same general scene as the previous image however the drone has moved approximately 800 meters north from the position in the previous image. Sun glint is no longer a factor. The pilot (author) is visible operating from beside the rear of his pickup truck at scene center on the right side of the road (western side) upon magnifying the enlarged image.

Western slope 7

Image acquired 17 October 2014. Western slope of Battle Mountain, overhead vertical image of a 19th century family cemetery from the Wood estate. It contains the remains of eight individuals including those of 1st Lieutenant Wood of the Virginia (Confederate) infantry.

Western slope 8

Image acquired 17 October 2014. Western slope of Battle Mountain, higher altitude and low oblique angle of the same cemetery, facing east. The ~2 m tall marble obelisk headstone of one of the female Wood family members is now evident in the front row of headstones.

Western slope 9

Panoramic image of the western slope of Battle Mountain that was created from a composite of 10 individual images acquired on 17 October 2014.

Post-Processing Images

Images were generally edited with Microsoft Paint, a free component included with Microsoft Windows version 7. Typical post-processing functions included resizing images to make them more Web-friendly (generally reducing image size to 20% of the original image size of 4384 wide by 2466 pixels high, which not only greatly reduced the amount of screen space taken up by an image but also importantly reduced the file size from approximately 6 MB to less than 800 KB. This allowed the files to load much faster and consumed far less bandwidth, which is especially important for mobile users who may be accessing the Internet with 4G or 3G cellular data networks.

Additional post-processing capability was utilized with an inexpensive piece of commercial software called PTGui, version This software is specifically designed to stitch together individual images taken from different segments of the same scene and mathematically create a calculated composite panoramic image. While PTGui has some limitations, the author generally found it easy to learn to use and quite powerful for working with a series of individual images of reasonable quality. Below is an example of the output composite panoramic image created by PTGui before final post-processing cleanup. Because of different amounts of visible sky in each image making up the composite, there is a great deal of variation in visible sky shown in each segment. This needed to be cleaned up in the post-processing stage after PTGui generated the composite panoramic image.

Because the same camera system was generating the same resolution images for each frame of the composite, minimal manual adjustments were necessary when creating the composite with PTGui. Some adjustment was necessary at the horizon, where the PTGui software was not able to always accurately assess the appropriate link point. This was primarily due to the complex orogenic terrain visible on the horizon that made it impossible for the software to always locate an appropriate linkage point between the still images. This required a series of manual dragging and dropping operations across the composite image to assist the software in making the correct composite lineups. Once that was accomplished the software was the able to create the final panoramic image file seen below:

This was a relatively large composite image file which clearly needed some additional post-processing edit cropping in order to be presentable. Because of the large file size of the high-resolution composite (approximately 12 MB) it was too large for Microsoft Paint to be used to crop and edit the image. The author used VirtualStudio, a shareware image editor tool with surprisingly powerful capabilities, to crop the final image, add the title and copyright text to the lower right corner, and create the final panoramic image file. VirtualStudio lies approximately in the middle of the spectrum of professional image editing software capabilities, with Microsoft Paint being the least capable and Adobe Photoshop being among the most capable (and most expensive) image processing software tools.

Western Slope Composite

The final low-resolution cropped composite panoramic image.


It is apparent from the quality of these images that multirotor drone UAVs could be an indespensable and inexpensive addition to the SFAP toolkit. The learning curve was relatively shallow and allowed the author to single-handedly operate and manage the SFAP platform in a short amount of time. Typical SFAP flight missions were conducted in just a few minutes, in fact the drone operation and performance was so efficient that the 30 minute flight time provided by the lithium polymer batteries was usually more than sufficient for each image gathering mission. The author routinely carried multiple charged spare batteries with him but rarely had to make use of them. This was primarily due to the flight performance of the drone and also its ability to provide a real-time video display of what the drone camera was seeing during flight. This allowed the pilot to rapidly place the drone into the correct flight position and obtain the desired images.

However, knowledge of the atmospheric and radio system limitations is key to successfully operating this drone system without loss or damage to the UAV. The author also recommends first obtaining an inexpensive (approximately $20) toy-grade indoor-use-only infrared-remote-controlled helicopter to first experiment with before launching the far more expensive multirotor UAV drone system outdoors. The toy-grade infrared remote controlled helicopters feature the same wireless flight control system layout (minus the Wi-Fi camera and telemetry system) and could build confidence and provide useful experience with learning helicopter-style remote controls without worrying about making a costly mistake.

Literature Citations

(1) Hanford, S., Long, L., Horn J., 2005, A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle (UAV), Aerospace Research Central, AIAA Meeting Papers, American Institute of Aeronautics and Astronautics

(2) U.S. Geological Survey, 2003, Robertson River Igneous Suite; Battle Mountain Alkali Feldspar Granite - felsite USGS Mineral Resources On-Line Spatial Data

This webpage is copyrighted by Thomas A. Woolman.
All original content is © copyrighted by Thomas A. Woolman, with permission granted to Emporia State University for academic use with attribution to the author.