Mace UAV Research Group

Mace UAV Research Group

School of Life Sciences

Rain Forest Survey Using

Unmanned Aerial Vehicles (UAV)

Authors:

Bill Crowther – [email protected]

Khristopher Kabbabe – [email protected]

Gareth Roberts – [email protected]

Rain Forest Survey Using Unmanned Aerial Vehicles (UAV) [2012]

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1. INTRODUCTION

1.1. MOTIVATION

Unmanned aerial vehicles are complex systems created to substitute the human in missions deemed

as dirty, dull or dangerous. With the current maturity of the technology and the high level of

demand, UAVs are finding their way into civilian applications: aerial photography, search and rescue,

among others. With this tendency due to increase academics are now interested in research

opportunities to develop innovative UAV solutions and applications.

1.2. MISSION

To assess the feasibility of creating a high resolution map of the surroundings of the

Timburicocha Research Station using Unmanned Aerial Vehicles (UAVs).

To assess the requirements for creating a map detailed enough to identify species of trees.

1.3. OBJECTIVES

This report aims to inform on the tasks carried out by the UAV Research Group on the Ecuador field

trip, on the lessons learn along the way and to reflect on the next step.

To achieve these objectives this report will review:

The operating conditions in the rain forest.

The missions flown and the results obtained.

The lessons learned and the way forward.

As a secondary objective this report also aims to analyse the current technology used obtain and

post process the orthophotographs obtained and to reflect on the camera settings needed for

orthophotography. These will be based on the experience gained.

1.4. APPLICATIONS FOR AERIAL PHOTOGRAPHY IN THE BIOLOGY FIELD

1.4.1. MAPPING

Perhaps the most obvious and exploited use of aerial photography, the images could be used to

create a detailed map of the region to a much higher resolution to that offer by Google Earth. It can

be used to map the river, walking routes, road planning and further development of the areas

surrounding the research station.

1.4.2. SPECIES CENSUS

With the aid of image recognition software, it would be possible to create a census of the flora found

in the forest. By training the software of the different families of trees it would be possible to tell

how much of an area is covered by what plant. It could also be used to create a census of the fauna

found on top of the canopy.

1.4.3. DEFORESTATION MONITORING

Suggested by one of the students in the field trip, UAVs could be used to research on the effects that

deforestation have in the change of biodiversity in the region.


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2. THEATRE OF OPERATION

2.1. Location

The Timburicocha research station is located S: 0.483281 W: 77.284390 2km north of the San Jose

de Payamino community and 141km east of Quito. The station is 292m above sea level. Its weather

is the typical rain forest weather. Figure 1, below, shows the Timburicocha Research Station.

Figure 1: Timburicocha Research Station

2.2. TAKE-OFF AND LANDING CHALLENGES

The area is clear from buildings and is relatively inhabited (ideal conditions for UAV flying), rough

terrain and tall buildings where the primary concern when operating UAVs. To operate the aircraft,

part of the research station had to be prepared.

An area of around 30x15 meters, shown below in Figure 2, was cleared from tall grass, as to

uncovered roots and other features which might damage UAVs while landing. Branches of trees

located on the river side of the station where taken down as to increase the field of view (yellow

area) of the operator and to ease manual approach and landing manoeuvres.

Figure 2: UAV Strip at the Research Station


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Figure 3 shows a topographic map of the area of take-off and landing. The map shows some of the

obstacles to avoid during take-off and landing manoeuvres. Green lines show the approximate

canopy height, while purple lines show high-value obstacles.

Figure 3: Topographic map of the area of operation

2.3. MAINTAINING UAVS

For maintaining and preparing the aircraft, we were assigned an area located in a building adjacent

to the strip. For our purpose, the room was fitted with shelving made out of bamboo, for columns,

and planks of wood. Using the same materials, 3 work benches were also fitted. The room is shown

below in Figure 4.

Figure 4: Timburicocha UAV Research Lab


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3. MISSIONS AND RESULTS

3.1. OVERVIEW

For this project, three missions were defined: an aerial survey over the canopy using fixed winged

UAV, vertical survey within the canopy using rotary wing aircraft, and a point to point survey over

the canopy using FPV and long range radio equipment.

3.2. AERIAL SURVEY

For the aerial survey the main objective was to create a high resolution map of the surroundings of

the Timburicocha Research Station. The sample image, below in Figure 5, shows the research station

from an altitude of 368.02 above sea level, 76 meters above ground level.

Figure 5: Timburicocha Research Station from the air

The image shown above was used during the field trip by the research station manager to plan for

the new walking paths being constructed. It will also be used to plan for future eco-friendly drainage

system.

To take the images the camera had to be manually started from the ground with the correct

settings. Then, the aircraft was manually taken, by a pilot, to the desired height, typically around 75

to 100 meters above ground level. At this point the second pilot, fitted with FPV equipment, would

take over and fly the aircraft on a straight pattern up and down the river and around and over the

research station. A manually stitched map, Figure 6, shows the area covered within the first flights.


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Figure 6: Manually Stitched Map of the Surroundings of the Research Station

The orthographic map above, also shown as appendix A, was stitched by two biology students on

site. Within the map several features a recognisable, such as the research station, the river, the bed

of rocks opposite to the station, river deviations around the rocks and going into the forest, as well

as several types of trees.

Although this first iteration was done manually, the final iteration of the map will be processed using

a mix between control points, GPS positioning and manual processing. An explanation of these

approaches and why they must be used is given in appendix G.

Figure 7, below, show an orthomosaic map composed by over 1100 images. The map was processed

using the latest version of the Pix4D cloud base software (appendix H). Although not entirely correct,

the software is able to stich most of the 1100 image that were uploaded to the cloud. The main

difference with HUGIN is that Pix4D reads and uses the GPS and IMU information (when available) to

pre-allocate the images and then it looks for control points. A larger version of the image is

presented as appendix B.


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Figure 7: Orthomosaic map of the Timburicocha Research Station using Pix4D

The area covered in the manually stitch map is yet to be determined as more images are being

added to the final version. However it is estimated that around 500 x 800 meters was covered by

these flights. For the Pix4D map an area of just over 0.7 Km2 is covered.

To take the photos, the camera was setup manually with specific settings being applied before each

flight. Appendix E shows the camera settings used and offer recommendations for each setting

based on the experience obtained on the field; Appendix F, shows the field of view calculations

made to assess the overlapping of the images, necessary in order to visually match images.

3.3. Vertical Survey The main purpose of this mission was to assess if a very high resolution vertical map could be

created using rotary wing aircraft, using a tree as the subject of interest. Applications might include

fauna census, and 3D modelling of a specific tree.

For this mission, two flights were made; the first flight was made using the T-Rex 600 equipped with

the Samsung NX100 camera, the second flight using a MicroKopter equipped a stabilized platform

with a Canon compact camera. The technique and settings used to take the images on both

helicopters was the same as for the fixed wing aircraft

The main conclusion of this mission is that when taking into account the endurance, operating space

and ease of maintenance and operation the multicopter is a better choice.

3.4. Point 2 Point Survey This mission had as its main objective to test and assess the range and reliability of the long range

radio equipment, in specific: radio receiver, video transmitter, and telemetry modules. The


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secondary objective was assessing the feasibility to do survey along a path, rather than on a pattern

around a specific area.

To test the equipment beyond line of sight, a flight plan which consisted on a straight line between

the research station and the San Jose de Payamino community was traced; the distance between

waypoints was of 2km. The objective was to assess wherever there was sufficient range on the radio

equipment as to make the journey without problems and to document the trip using HD video from

a front facing GoPro2 camera, below.

Figure 8: Long range FPV kit

For this mission a pilot would take-off and get the aircraft to a safe altitude before handing over to

the FPV pilot. Although the control transmission was lost before reaching the town, it was

demonstrated that the 900MHz video equipment would be adequate for this type of mission. It also

made evident the requirement for a robust and fully tuned autopilot.

Regarding the point to point survey, it was demonstrated that these type of survey would be useful

for application where a complete area survey might not feasible due to time, economic or technical

constraints. Mapping the river, marking roads between research stations to other points of interest

are some of the possible applications of point 2 point survey.


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4. PROPOSED APPLICATIONS FOR UNMANNED VEHICLES IN THE FIELD OF

BIOLOGY

4.1. Real-time spotting UVs could be used as a complement to camera traps, where after the camera has located a subject

of interest, a nearby unmanned vehicle, would be deployed to track, spot, or chase the subject of

interest. This type of camera traps could be used for water and aerial subjects.

4.2. Distance Live Research

Using a small fleet of different unmanned vehicles it would be possible to explore terrain and survey

areas on-demand from anywhere in the world. This idea proposes that a researcher could use this

fleet for surveying, surveillance and exploratory purposes.

In the case of the students, they would be able to explore the terrain before they got there.

Researchers could have surveying mission running several times a week.

Some of the requirements to make this feasible would be:

Autonomous systems should be able to perform complete mission and return to a charging

pod autonomously.

Ground control stations and mission management software should be sufficiently de-skilled

as to make the technology accessible to non-specialized users.

A fast internet connection and an internal network would need to run within the research

station.

A person, preferably a local from the area, would need training on the maintenance and

repair of these systems.

Individually, all the technology required to achieve this already exists. It is proposed that, by

combining the technology, autonomous unmanned systems could be used as research assets in

various fields, including biology, terrain survey, surveillance, site maintenance, atmospheric sciences

and many more. It is also proposed that the ability to do these tasks remotely in remote places

would attract research from all around the world.

4.3. Application specific layer for Google Earth

Using some of the features available within Google Earth Pro and the data collected using unmanned

systems, it is proposed that application specific layer could be created to visualize and share the data

obtained. For example, with the use of an unmanned water vehicle, river flow, diversity and

properties could be mapped using Google earth to share with researchers and students information

about the Payamino River.

In addition, by using a database and the data obtain from various passes, it would be possible to

develop a timeline showing the changes as time passes by.


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5. Conclusion

5.1. LESSONS LEARNT

During the course of the field trip numerous lessons were learned.

It is possible to transport sensitive equipment on a standard luggage when appropriate

padding is used.

Small UAVs such as the ones used within this project can be transport on civil commercial

airliners, and it is cheaper to pay for them as extra luggage than using a currier to deliver.

Although helicopters have more economical spare parts, compared to multicopters, they are

not well suited for missions in rough terrains.

The radios, cameras, ground control stations, tools and aircraft used were not affected by

environmental conditions such as humidity and heat.

Leaving a down facing camera in automatic mode will result in blurry over exposed images

or sharp under exposed images.

For aerial site survey an autopilot is a requisite.

5.2. WAY FORWARD It is common at the end of every project to say, “I wish I could go back and do it again knowing what

I know now” and this is no exception.

By configuring a complete navigation system it would be possible to maximize the time

spent on the air taking images. By employing a tuned autopilot system a grid could be drawn

around the research station, mapping a considerable larger area at various heights at

different ground resolution, creating several maps.

A custom script would be installed in the aircraft camera. The script would contain the exact

parameters and settings as per the mission requirements.

By utilising the point 2 point style mission several paths could be drawn on maps, routes to

the armadillo mountain and the San Jose de Payamino could be detailed and given as

interactive foot maps.

3D detailed models of trees could be created using multicopters.


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6. Appendices


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APPENDIX A:

Manually Stitched Mosaic of the Surrounding of the Timburicocha Research

Station


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APPENDIX B:

Orthophotography Mosaic Automatically Stitched Using Pix4D


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APPENDIX C:

Packing and Transportation to the Research Station

PACKING THE EQUIPMENT

From the fleet at our disposal (see www.uavs.mace.manchester.ac.uk/index.php/Methods/Fleet for

more details), when selecting which aircraft to take several factors were taken into account,

including:

Payload capability.

Ease of maintenance.

Performance (in specific, take-off and landing requirements).

Ease of transport.

Several quotes were requested from currier companies like DHL and FedEx with an average cost over

2000 for transporting the equipment. The cost did not include cases or packing material. Due to the

high cost of transportation, it was decided to take the equipment in the aircraft and pay for extra

luggage instead using curriers. Figure 9, below, shows how sensitive smaller equipment, like

cameras, were taken in ruggedized cases filled with foam and other parts and smaller aircrafts were

taken inside standard sized luggage.

Figure 9: Packing and protecting the equipment

Skywalker UAVs were individually packed inside the boxes where they are originally shipped on.

These were then taped together to form a unified large box, Figure 10. The dimensions were

approximately 30 x 120 x 80 cm.

Figure 10: Skywalker box at Quito International Airport

https://uavs.mace.manchester.ac.uk/index.php/Methods/Fleet


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GETTING THERE

FROM MANCHESTER TO QUITO: COMMERCIAL FLIGHT

As any other good, UAVs and equipment were loaded into a

Boeing 777. During this leg the equipment is subjected to changes

in temperature and pressure, rough handling by the luggage

handlers and stress concentrations by luggage placed on top of it.

FROM QUITO TO COCA: COMMERCIAL BUS SERVICE

The equipment was loaded into a passenger bus.

Equipment was not subjected to any stress during this 8

hours trip.

FROM COCA TO SAN JOSE DE PAYAMINO: RANCHERAS

Rancheras are pallet vans equipped with wooden benches and

roof. They are cheaper than buses and are able to go through

rough terrain while still transporting a large amount of people

(around 30) and goods. Equipment is mounted on top of the

roof and is subjected to stress created by the case on top of it.

Risk of falling of the roof is controlled by tighten the luggage

using elastic ropes.

SAN JOSE DE PAYAMINO TO TIMBURICOCHA RESEARCH

STATION: INDIGENOUS MOTORISED CANOES

Canoes represent the highest risk to the equipment. It is

safer to assume that the luggage and boxes will get wet. It is

advices that casing should be at least water resistant.


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APPENDIX D:

UAV Fleet

FLEET

SKYWALKER – FIXED WING UAV

The Skywalker is an off-the-shelve radio controlled aircraft that with the inclusion of an autopilot is

able to become a fully autonomous and capable UAV. Figure 11, below, shows one of the models

ready to be operated. The aircraft is shown mounted a bamboo monopole built by the members of

the local community.

Figure 11: Skywalker UAV "Cowboy"

SPECIFICATION:

Compatible Autopilot: Paparazzi, ArduPilot Mega.

Power System: 3014-1100kV Motor, 60A ESC, 9x6 pusher tri-bladed propeller, 4s 5000mAh

battery

Standard Payloads: Front Facing EO Camera, High-resolution down-facing EO camera, 5.8

GHz Video Transmitter, 2.4 GHz Telemetry Modem.

Payload Capacity: 1 Kg

Range: 20 Km

Endurance: 17 Minutes (Using a 4S 4000 mAh Li-Po battery)

Speed: 15 - 25 m\s

Operating Altitude: 15 - +700 meters (UK max legal altitude is 125 meters)

Wing Span: 1900 mm

Length: 1180 mm

Payload bay: 350 X 100 X 60 mm (L x H x D)

Applications: Area survey, Aerial photography.

Launch & Recovery Method: Hand-launched, conventional landing.

Figure 12 shows a 3 views drawing of the Skywalker UAV with its main dimensions.


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Figure 12: 3-View of the Skywalker UAV


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T-REX 600 – ROTARY WING VEHICLE

The 600 sized helicopter offered larger payload capability plus vertical take-off and landing. Its main

use was to take high resolution photography and video of trees from within the canopy. Figure 13,

below, shows the T-Rex helicopter in flight carrying 2 optical sensors, one for HD video and the other

for high resolution photographs.

Figure 13: T-Rex 600 Helicopter during testing phase

SPECIFICATIONS

Compatible Autopilot: Commercial stabilization unit.

Standard Payloads: High-resolution EO Camera, 1080p Video Camera.

Payload Capacity: 1.5 Kg

Range: 5 Km

Endurance: 3 - 15 minutes

Speed: 0 - +40 mph

Rotor diameter: 1347 mm

Length: 1160 mm

Payload bay: External - between landing skids

Applications: Area holding, survey, Tree sampling.

Launch & Recovery Method: Vertical Take-off and landing.

Although the helicopter provides excellent payload capacity due to its large excess power, it was

concluded that the amount of spare parts needed to service a helicopter, the skill level needed to

assemble, tune, operate and maintain it makes it a not optimal choice, especially when compare to a

multicopter.


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MICROKOPTER HEXA XL – HEXCOPTER UAV

The primary purpose of this aircraft was to complement the T-Rex when more precise (autonomous)

flight was required, or when longer endurance was needed. This vehicle was equipped with an

optical sensor with a DSLR size imaging sensor. Figure 14 shows the hexcopter while demonstrating

at the San Jose de Payamino community. The stabilize camera mount and video downlink proved to

be a useful assets in the field.

Figure 14: MicroKopter Hexa XL at the San Jose de Payamino community

SPECIFICATIONS

Compatible Autopilot: Commercial stabilization unit.

Standard Payloads: Stabilized HD HR EO sensor.

Payload Capacity: 1.5 Kg.

Endurance: 45 minutes

Speed: 0 - 30 mph

Operating Altitude: 0 - +100 meters

Rotor diameter: 6 rotors of 300mm in diameter each

Payload bay: External - between landing skids

Applications: Area holding, survey, Tree sampling.


This multi-copter is potentially more expensive than a standard helicopter. It is however, easier to

maintain, assemble and operate, it offers greater stability and flexibility than a helicopter.


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A.R. DRONE – OFF-THE-SHELF COMMERCIAL QUADCOPTER

The AR drone’s primary purpose was to provide training to the non-engineering crew and to be used

for low altitude vertical survey. The main feature of the drone is also its main limitation; it can be

controlled from a mobile device running IOS or Android OS via Wi-Fi. Hence, its operating range is

limited to the network range. This vehicle, shown in Figure 15, is capable of recording 720p quality

video to an external USB thumb drive. To operate the Parrot drone a landing pad, made out of the

top section of a plastic table, was taken when it was required to operate from rocky or rough

terrains.

Figure 15: AR Parrot Drone on landing pad

SPECIFICATIONS

Compatible Autopilot: Proprietary stabilization unit.

Standard Sensors: 720p resolution camera, low resolution down facing camera.

Payload Capacity: USB thumb drive.

Range: Wi-Fi range.

Endurance: 15 minutes.

Speed: 0 - 15 mph.

Operating Altitude: 1 - 200 meters.

Rotor diameter: 4 rotors of 230mm in diameter each.

Applications: Training, Area holding, Survey, Tree sampling.


A list of the Electro Optical (EO) sensors and the radio frequencies used for telemetry, video and

control transmissions used is given in detailed in appendix D.


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APPENDIX D:

Electro-Optical Sensors, Radio Frequencies and Settings Used

EO SENSORS

Down facing camera: Canon PowerShot SX230 HS with CHDK

Resolution: 12.1 Megapixels.

Focal range: 28 - 392 mm (35mm equivalent).

Sensor size: 1/2.3 inch CMOS.

Size: 105.7 x 61.6 x 33.2mm.

Weight: 223 grams.

Features: GPS Tagging, CHDK compatible

Front facing camera: SN777 Sony 1/3 inch CCD

Resolution: 550 TVL.

Size: 25 x 25mm.

Weight: 22 grams.

Specs: 5V, PAL format.

Features: Metal casing.

Long range FPV: GoPro HD HERO 2

Resolution: 11 Megapixels.

Video: 1080p Video recording.

FOV: 170, 127 and 90 degree.

Sensor size: 1/2.3 inch CMOS.

Size: 42 x 50 x 30mm (naked).

Weight: 167 grams (incl. housing).

Helicopter camera: Samsung NX100

Resolution: 14.6 Megapixels.

Focal range: 20 - 50 mm (35mm equivalent).

Sensor size: 23.4 x 15.6mm.

Size: 120.5 x 71 x 34.5mm.

Weight: 340 grams.

RADIO FREQUENCIES

By not being restricted to UK radio regulations we were able to test a variety of frequencies and

transmitting strengths for FPV video downlink, data telemetry and radio controls.

433 MHz was used to control the aircraft when flown beyond line of sight.

900 MHz was used on the long range FPV system.

2.4 GHz was used while flying within line of sight and for autopilot telemetry

5.8 GHz was used for short range FPV and to check down facing camera status while

operative.


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CAMERA SETTINGS USED

For Orthomosaic production several factors need to be taken into account to produce images that

will stitch properly. We can separate those factors into two categories: camera settings and flight

characteristics.

SHUTTER SPEED:

Setting: The higher the better

Reason: Pictures taken from a moving aircraft has to be taken as fast as possible to avoid blur and to shorten the interval between pictures.

Issue: As the shutter speed increases the amount if light that goes into the sensor of the camera decreases. This means that without the ideal lightning conditions the images will be underexposed. In addition, the poor optics quality found in cheap cameras further reduces the amount of light going into the sensor.

Solution: A bigger image sensor will be able to capture more light at the expense of an increase in size, weight and price. The second solution is to increase the sensitivity of the sensor to light (ISO) setting on the camera at the expense of noise in the image.

ISO:

Setting: As low as possible.

Reason: Increasing the sensitivity of the sensor introduces contamination (noise) on the image. This is the equivalent of burnt spots on film cameras.

Issue: When working on small platforms the weight limitation dictates that a compact sensor need to be used (1/4 inch sensor). This means that in order to shoot clear images the ISO will need to be increased.

Solution: Increase the sensor size.

FOCUS:

Setting: Auto focus off, manually set to infinity (above 15m for most cameras).

Reason: When using auto focus the camera reloads the lens to find the clearest image every time a picture is taken; this greatly increases the interval time between images, decreasing the overlap within the images. Turning the automatic focus off and manually setting the focus point to infinity will result in crisp images as long as the vehicle is flying at least 15 meters above the highest point of the area of interest.

Issue: None.

Solution: N/A

IMAGE STABILIZATION:

Setting: Off

Reason: Image stabilization is used to reduce the very low frequency shake caused by hand holding the camera in reduced light environments. The oscillation of the aircraft, although also relatively low frequency could throw the sensor out, reducing the crispness of the images. In rotary wing vehicles, for example, using this feature will result in useless data.

Issue: None.

Solution: N/A

INTERVALOMETER:

Setting: The shorter the better.

Reason: The more frequent you can take pictures the more overlap will exist between them, making it easier to find CPs and ensures the there are no uncover parts in the.


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Issue: The frequency at which pictures can be taken depends solely on the performance of the camera and, in some cases, the buffer time to save the image in the storage card. For compact cameras however, the bottle neck is the camera’s processing time.

Solution: High-end systems will usually include faster image processors and will be capable of taken images faster.


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APPENDIX E:

Calculation of Focal Length, FOV and Ground Resolution

FOCAL LENGTH

The Focal length is the distance between the mirror of the lens and the sensor of the camera. Due to

historical reason it is usually given in terms of 35mm, in other word, what the focal length would be

if a 35mm sensor (or film) was being used. As entry and mid-level DSLRs and compact cameras are

not 35 mm, often a cropping factor needs to be taken into account.

The cropping sensor is calculated using the following relation:

FIELD OF VIEW

The field of view of the image is the total projected area being photographed. Figure 16, below,

shows the geometrical relation required to calculate the field of view.


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Figure 16: Field of View Geometry

The relation above is used to calculate the FOV in the X and Y direction. By multiplying both the total

area being photographed per image is calculated.

GROUND RESOLUTION

The ground resolution is simply a quantitative description of how detailed the image will be in terms

of meters or centimetres per pixel.


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APPENDIX F:

Review of current post-processing techniques and software for aerial images

COMMON REQUIREMENTS

Most automated stitching software has similar requirements when it comes to the technique or

settings used to take the pictures.

Images need to be taken from one reference point (approximately same altitude), otherwise more computational time is required to align and resize images.

Aircraft should be in a stable straight flight, pictures taken while banking are useless for 2D maps and available software does not cope well with images taken from different perspectives.

Similar exposure across all the pictures, as control points might “disappear” in over exposed or under exposed images.

Images most have some overlap between them (best result being achieved when overlap is greater to 50%)

TECHNIQUES

CONTROL POINT BASED STITCHING

This technique, widely used for stitching images, relays on algarithms that seek for common

“features” present in overlapping images. It then align pictures based on those control points (CPs).

Pros:

Very efficient over urban areas, where clear defined lines in buildings, cars and intersections are used as CPs to merge the images.

Most software use this technique.

Can be done manually without any software.

Very easy to improve accuracy by manually adding CPs.

Cons:

Computationally expensive as the logarithm compare every permutation images submitted to it.

Inaccurate for rural areas, where roads and defined lines are inexistent.

When dealing with large number of images, manually adding CPs become tedious.

GPS + IMU + CP STITCHING

This technique makes use of the GPS feature of some cameras (via their Exchangeable image file

format (EXIF) data or GPX log of the autopilot) to first align the pictures based on the approximate

location where they were taken and then applies CP algorithms to neighbour images. This greatly

reduces computational time at the expense of the additional equipment required. By knowing the

GPS location of the area being mapped, adding features to the new map is relatively easy, one

example being the addition of elevation data to create Digital Elevation Models (DEM). In addition

when IMU data is available, images taken from an object at different perspectives can be used to

construct 3D models.

Pros:

Specifically design for Orthophotography


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All positive aspects of CP based stitching plus:

Computational time is greatly reduced by pre-placing images in their approximate location based on GPS data.

If altitude, compass, focal length and sensor size is available from the EXIF data, software can perform transformation on the images to, not only put them in their correct location, but also rotate and resize before aligning based on CPs.

When combined with IMU data 3D models can be constructed.

Cons:

Still computationally expensive when large number of pictures is used.

More expensive kit required on the aircraft (camera with GPS or GPS receiver on aircraft).

GPS data does fluctuate and if it is possible that location of some images is off.

When used in areas with “hard to define” CPs alignment is often not accurate.


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APPENDIX F:

Review of Post-Processing Software Used

HUGIN

HUGIN is an open source GUI front-end for Panorama Tools (command-line based stitching

software). It works by merging images with common control points together.

One of the reasons why CP based algorithm fails in rural areas is because of the lack of distinctive

features. In an urban environment a building surrounded by a park or a street is easily

distinguishable, Figure 17, below, shows how HUGIN has automatically found 20 CPs, enough to

merge the two images together.

Figure 17: 20 CPs automatically found by HUGIN in an urban environment

An issue with this approach is that in the rural environment there is no distinctive shape popping out

of the green background. Figure 18, below, shows how HUGIN has failed to acquire control points.

This shows that a more complex algorithm is needed to detect less obvious control points, based on

textures rather than edges and straight lines.

The image below also serves to demonstrate the effect of perspective. This feature can be used if

stereoscopic images are to be created. However, when mapping this is undesirable as it increases

the difficulty in finding common control points. To minimize the difference in perspectives the focal

length of the camera needs to be increase or the altitude should be increase.

Figure 18: Visible overlap between two images taken during the Ecuador mission


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What is needed is an approach that not only looks for control points, but that is capable of adapting

itself based on the content being processed. This is not to be confused with the content awareness

feature offered by some photograph software (which is harmful for this specific application).

PIX4D

A cloud-base aerial image processing solution which uses proprietary algorithm to stitch images

based on CPs + GPS + IMU information. The company offers a free trial where the software will show

a preview of the Orthomosaic. If the map is stitched successfully pix4D will give you a quote on the

final map. To test the software a sample of the last 144 images was uploaded to their cloud.

Figure 19: Pix4D sample image

Figure 19, above, shows the free preview of the images processed by the software. The images

uploaded to their cloud were processed with the latest version of their algorithm (as of September

2012).

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Mace UAV Research Group