Developing a Low-Cost Aeromagnetic Surveying System

An Undergraduate Senior Thesis

Submitted in Fulfillment of Bachelor of Science Degree in Geology

University of Nebraska-Lincoln

By Erik Jacobson, BS

Geology College of Arts and Sciences

May 8th, 2020

Faculty Mentor: Irina Filina, PhD, Geophysics

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Table of Contents

Abstract ................................................................................................................................ 3

Acknowledgements ............................................................................................................... 5

Introduction .......................................................................................................................... 6

Chapter 1 Assembling the Aeromagnetic Surveying System .................................................... 8

Magnetometer Overview and Tests ................................................................................................8

Unmanned Aircraft System Overview and Test ............................................................................. 14

Rigging ........................................................................................................................................ 19

Chapter 2 Testing The System .............................................................................................. 23

Initial Test Flight .......................................................................................................................... 23

Primary Test Location and Geology ............................................................................................... 27

Northern Bounding Fault Survey .................................................................................................. 33

Chapter 3 Working With Data .............................................................................................. 37

Processing Raw Data .................................................................................................................... 37

Data Analysis ............................................................................................................................... 46

Conclusion ........................................................................................................................... 51

References........................................................................................................................... 54

Appendix A: Workflow for ENVI-MAG WALKMAG and UAS Operation .................................. 57

Appendix B: Aeromagnetic Survey Packing List .................................................................... 60

Appendix C: UAS Based Aeromagnetic Survey Workflow ...................................................... 61

Appendix D: MATLAB CODE ................................................................................................. 63

Appendix E: Lessons Learned ............................................................................................... 65

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Abstract

Geoscientists conduct magnetic surveys to locate subsurface geologic structures by

measuring the geomagnetic field with a device called a magnetometer. An airborne magnetic

survey is performed by mounting one or more magnetometers onto a payload-carrying aircraft

such as a helicopter, airplane, or unmanned aircraft system (UAS). UASs are utilized as platforms

to conduct high resolution, efficient, and versatile surveys because of their low altitude and

variable speed capabilities. A low-cost UAS based aeromagnetic surveying system was designed,

assembled, and flown by the UNL Geophysics Team for the purpose of identifying geologic

structures across Nebraska. The Scintrex ENVI PRO magnetometer was mounted upon a DJI

Matrice 600 Pro UAS. Several ground walking surveys were performed at Mable Lee Field within

the University of Nebraska’s city campus with the magnetometer alone to determine the most

favorable settings for the forthcoming flight. The optimal distance from the instrument’s sensor

to the UAS was measured to minimize magnetic noise emanating from the aircraft. Using these

parameters, the magnetometer was mounted upon the UAS and flown with help from the

University of Nebraska’s NIMBUS Lab at their test site. This initial testing of the equipment

resulted in detailed and comprehensive operating procedures and workflows for instrument

operation and data processing.

The surveying system’s primary test over a known geologic structure was performed on

November 9th, 2019. The survey was conducted to map the Northern Bounding Fault of the

Midcontinent Rift System in eastern Nebraska that represents a contact between rocks of

strikingly different magnetic properties. Two separate flights were piloted in a 200x200 meter

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area near Venice, NE. The ambient magnetic field was subtracted from ENVI PRO’s readings to

find the magnetic anomaly. The positioning data recorded by the UAS and the magnetic anomaly

were merged to compile a magnetic anomaly map. Statistical analysis of the magnetic readings

at the crossing points of the two flights allowed examination of the survey’s accuracy. The

Northern Bounding Fault was interpreted based on magnetic anomaly variations in the composed

map. A previously published aeromagnetic map showed a similar trend in magnetic anomaly, but

the new system’s data was consistently ~30 nT lower. At this particular location, the fault is

inferred to deviate from the published trend. This suggests the fault may be segmented but this

hypothesis requires further investigation. The operating procedures for the new low-cost UAS

based aeromagnetic platform were finalized and a complete packing list for future fieldwork was

composed.

Possible targets for future surveys include the adjacent blocks of the Northern Bounding

Fault, old wells, and the recently reactivated fault system near Arnold, NE. This new UAS based

aeromagnetic surveying system will increase the capabilities of the UNL Geophysics Team to

acquire high-resolution magnetic data over difficult terrains where walking is challenging.

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Acknowledgments

Special acknowledgments for the completion of this research go to the University of

Nebraska-Lincoln Department of Earth and Atmospheric Sciences. Most importantly, Dr. Irina

Filina for providing an incredible opportunity for this research to be conducted and guidance

throughout its accomplishment. The University of Nebraska-Lincoln’s UCARE undergraduate

research program is also acknowledged for providing funding to the author. Deepest gratitude

goes to the University of Nebraska-Lincoln’s NIMBUS Lab, especially Dr. Carrick Detweiler for

providing assistance with Unmanned Aircraft Systems and Ashraful Islam for working as a pilot

and giving guidance on rigging and operations. The author would also like to give special thanks

to the Lyman-Richey Co. for giving the UNL Geophysics Team access to the survey area.

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Introduction

Recently Unmanned Aircraft Systems (UAS) have evolved to fly precise missions that give

the pilot complete control of flight altitude, speed, and coordinates (Cunningham, 2018). UASs

have also become powerful enough to carry a professional’s equipment, such as cameras in the

photography industry (www.dji.com). These capabilities have allowed geoscientists to preform

detailed aeromagnetic surveys that can be conducted over many types of terrain. Slow flight

speeds and low altitudes permit the recording of accurate data readings, although the flight time

may be limited by battery life. Detailed magnetic anomaly maps can be composed from airborne

magnetic data. However, pre-built commercial UAS based platforms, such as MagArrow

(www.geometrics.com/product/magarrow/) are unaffordable for educational use (~$40K in

2019, personal communication).

The primary objective of this study was to assemble and test a low-cost UAS based

aeromagnetic surveying system. The motivation for this project was the 2018 severe spike in

localized earthquake activity that was recorded near Arnold, Nebraska from February 9th until

December 13th (Filina et al., 2018). There were 28 earthquakes recorded that ranged in

magnitude from 2.0 to 4.1. The source of the stresses that caused these earthquakes remains

unknown, but magnetic surveys could be used to map the reactivated fault system.

Aeromagnetic surveys using a UAS would be the most effective technique to collect data due to

the UAS’s ability to transverse over agricultural fields and vegetation. Therefore, a low-cost

surveying system would be optimal to study the cause of 2018 Arnold seismicity.

http://www.dji.com/http://www.geometrics.com/product/magarrow/

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The study has three principal objectives to be successful. First, a proper UAS was selected

to carry the Scintrex ENVI-Pro magnetometer adapted for this project and the appropriate flight

settings were determined. The DJI Matrice 600 Pro (Matrice 600 Pro manual, 2018 ) was

purchased for this project. Second, the magnetometer was mounted upon the UAS. The sensor

of the device is sensitive to the magnetic field emanating from the UAS and records it as unnatural

magnetic noise that distorts magnetic readings. Proper mounting ensures that the equipment is

secure and the sensor is positioned far enough away from the UAS to minimize the noise. The

final objective of this study was to test the assembled aeromagnetic surveying platform. At first,

a local test was conducted to examine the reliability of the collected data. This was followed up

by the primary survey over a known geological structure, namely the Northern Bounding Fault

(NBF) of the Midcontinent Rift System (MCRS). As a result, detailed and comprehensive

operating procedures were composed to conduct geophysical surveying. These were compiled

into workflows to be used by future operators in forthcoming fieldwork.

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Chapter 1 Assembling the Aeromagnetic Surveying System

Magnetometer Overview and Tests

The first objective of the study was to assemble the UAS based aeromagnetic surveying

system. The UNL Geophysics Team’s magnetometer was adopted and the appropriate UAS was

purchased as a carrier. The instrument for this new system was the Scintrex ENVI PRO

magnetometer (Figure 1). The ENVI PRO is used for environmental, geotechnical, archeological,

and mineral exploration magnetic surveying. It is battery powered, lightweight, and durable

which makes it ideal for aeromagnetic operations with a UAS. This model of magnetometer was

introduced in 1994 and possesses an interactive menu using an LCD screen, a WALKMAG walking

mode, internal memory of up to 188,000 data readings, and a cold-weather resistant

rechargeable 12-volt battery (ENVI PRO Manual, 2009). These features were innovative at the

time of the ENVI PRO’s production and years later the device is still reliable as an appropriate

low-cost option for research and educational use. WALKMAG mode is trademarked by Scintrex

and is a setting that allows continuous data acquisition while using the device on the move. This

setting is critical for aeromagnetic surveying where stop and go style data collection cannot be

utilized. Other than WALKMAG, the ENVI PRO can be configured as a magnetic base station. A

gradiometer mode is also available but requires the use of two separate sensors.

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The ENVI PRO is a proton precession magnetometer. Figure 2 shows the components of

a proton precession magnetometer. The sensor is filled with a liquid rich in hydrogen atoms

surrounded by a solenoid. Orienting the sensor to the Earth’s magnetic north pole is critical for

the correct magnetic field alignment and accurate readings (see the North marker on the sensor

in Figure 1). When direct current is applied to the solenoid within the sensor, a strong magnetic

field is produced. Protons contained in the liquid become aligned with the direction of the

applied field. When the current is turned off, the Earth’s magnetic field generates torque upon

the protons. The protons begin to spin in response to this torque generating a small AC current

in the coil. This current is proportional to the angular frequency of the spin of the protons, which

in turn is proportional to the strength of the total magnetic field. The total magnetic field is a

superposition of the Earth’s ambient field and the induced magnetic anomalies from subsurface

features with anomalous magnetic properties (Lillie, 1999). This AC current is the physical

Figure 1. Photo of the Scintrex ENVI PRO magnetometer with sensor. Notice North marked N on sensor for orienting the sensor to the Earth’s magnetic field. Pen is included for scale.

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quantity that is measured and recorded by the instrument as total magnetic intensity (TMI)

reading. In WALKMAG mode, this is occurring at a rate of either 0.5, 1, or 2 readings per second

depending on the setting the user has chosen. A proton precession magnetometer is accurate

within 1 nT (ENVI PRO Manual, 2009).

The ENVI PRO can be operated with different settings for various types of applications.

Before the magnetometer was mounted upon the UAS, several ground experiments were

conducted to define the correct settings for forthcoming aeromagnetic data collection.

Meticulous reading of the Scintrex ENVI PRO manual constrained these settings before any

fieldwork was done. There are three different operating modes for this magnetometer: basic

mode, search mode, and advanced mode. Search mode allows for visualization of the magnetic

field but does not record it, while basic mode does not allow any customization of the survey

parameters. Therefore, they were removed from consideration for operating procedures.

Figure 2. Simplified schematic of a proton precession magnetometer showing hydrogen within the solenoid of the sensor, the different parts that power the device, and the console (counter) that records TMI data. Figure from pburnley.faculty.unlv.edu.

https://pburnley.faculty.unlv.edu/GEOL442_642/MAG/NOTES/MagNotes23proton.html

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Advanced mode gives the user total control of the survey parameters to customize the settings.

WALKMAG automatic data acquisition can be enabled in this mode by activating the cycle repeat

and the auto record settings.

With advanced mode selected for aeromagnetic surveying, the correct sampling rate was

determined. In WALKMAG mode, three sampling intervals can be selected: 0.5, 1.0, and 2

readings per second. To determine the correct rate for aeromagnetic surveying, the different

rates were each tested along the same profile. Mable Lee field on the University of Nebraska-

Lincoln’s (UNL) campus was selected for this test (Figure 3). 0.5 readings per second (2 second

sampling rate) gave the best results for a brisk walking pace (~1.5 m/s) similar to the flight of a

UAS (Figure 4).

Figure 3. Google Earth image showing the survey profile of Mable Lee Field on UNL’s campus, where sampling rate experiment was conducted.

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Figure 4a. Magnetic anomaly for the Mable Lee profile (shown in Figure 3) recorded with three different sampling rates. Magnetic anomaly was calculated by subtracting the ambient magnetic field on the day of the survey which was 53032 nT on April 2nd 2019 (358 m elevation) from the total magnetic intensity data taken by the ENVI PRO. Notice sporadic data collected with 0.5 and 1.0 s sampling rates at ~1.5 m/s walking speed.

Figure 4b. Same data as Figure 5a but showing a 2 second sampling rate (0.5 readings per second) only. This is the optimal setting and was selected for aeromagnetic surveying.

A B

A B

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Repeatability of the ENVI PRO was also examined by comparing data from three separate

tests along the same profile at Mable Lee (Figure 5). This revealed a shortcoming in the device,

namely the lack of a global positioning system (GPS). To find the distance along the profile, the

data was interpolated across the 86 m line causing some offset in the graphs. However, this

weakness can be corrected if the user uses a GPS that has the ability to record a timestamp. The

ENVI PRO records a timestamp, and the internal clock can be set precisely with another device.

Using time, GPS data and magnetic data can be merged. The UNL Geophysics Team at the time

did not possess a handheld GPS for use with a walking survey. Luckily, the DJI Matrice Pro UAS

records a timestamp from three onboard GPSs. Therefore, the aeromagnetic surveying system is

capable of recording both the magnetic field and positioning data.

Figure 5. Testing for repeatability of data at Mable Lee using a 2 second sampling rate along the same 86 m profile shown in Figures 3 and 4. Notice the offset between the readings due to interpolation of the data across the line.

Offset

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Unmanned Aircraft System Overview and Test

The UAS used in this project is the DJI Matrice 600 Pro (M600; Matrice 600 Pro Manual,

2018; Figure 6a). This UAS has six rotors, a carbon fiber frame and landing gear, three GPS

systems, and is powered by six intelligent flight batteries. It is designed to be a payload-carrying

system for commercial use and can carry up to 6 kg safely upon the center frame. The M600 has

a maximum flight speed of 18 m/s, a top ascent speed of 5 m/s, a descent speed up to 3 m/s, and

can fly in a max wind resistance of 8 m/s. Six intelligent 22.2 V flight batteries are included with

the M600. For the aeromagnetic surveying system, twelve upgraded batteries were purchased

with a higher energy capacity of 22.8 V. A graph showing the flight time using these batteries is

given in Figure 6b. These batteries discharge themselves when not in use to avoid damage.

Charging time using the included battery charger is ~50 minutes.

Figure 6a. The DJI Matrice 600 Pro UAS composed of six rotors, three GPS, six intelligent flight batteries, and carbon fiber frame. Figure from Matrice 600 Pro Manual (2018).

GPSs

Landing Gear

Intelligent Batteries

Mounting Frame

Rotors

15

The M600 is operated by a 2.4 GHz remote control that has a transmission distance of up

to 5 km. A smartphone or tablet is attached to the remote to run the primary control application

called Ground Station Pro. For this research, an iPad was utilized to operate this application.

Within Ground Station Pro, missions can be designed by inputting flight waypoints and

parameters such as speed and altitude. The M600 can also be operated manually by joysticks on

the remote control (Figure 7). The take-off of the M600 must be manually controlled by the pilot

before a Ground Station Pro mission starts. The pilot also must be able to take over the flight with

the remote control in case of an emergency or a mistake in the mission design.

Figure 6b. Graph from www.dji.com illustrating the flight times against a payload for two different battery types. The TB47S configuration is the 22.2 V batteries and the TB48S configuration is the 22.8 V batteries. The ENVI PRO’s total weight is 3.4 kg (ENVI PRO Manual, 2009) giving a flight time of roughly 18 or 22 minutes depending on battery configuration.

http://www.dji.com/

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Figure 7. Example of iPad setup for usage of Ground Station Pro application. Figure from https://www.dji.com/ground-station-pro.

Joysticks

https://www.dji.com/ground-station-pro

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Metallic parts and electromagnetic fields produced by the wires in the UAS create

magnetic noise that is picked up by the ENVI PRO’s sensor. This magnetic noise must be carefully

assessed and accounted for in the design of an aeromagnetic system. Therefore, before

mounting the magnetometer upon the M600, the proper sensor distance was found (Figure

8)(Jacobson and Filina, 2019). An experiment was conducted on April 10th, 2019 at the 84th and

Havelock UAS test field with permission and assistance from the UNL NIMBUS Lab. A tape

measure was utilized to find the distance between the powered UAS and the ENVI PRO sensor.

Noise measurements were recorded as the sensor was placed in different positions. To minimize

noise from the UAS, the sensor needs to be at a distance of at least 0.66 m away.

Figure 8a. Magnetic noise measured by ENVI PRO at different distances from UAS from Jacobson and Filina (2019). Noise is a unitless value recorded by the magnetometer in response to outside electromagnetic interference (ENVI PRO Manual, 2009). The noise is minimized at 66cm or 0.66 m. The distance from the ground to the mounting frame is pointed out in this figure as the furthest distance from the bottom of the drone.

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Figure 8b. Photo of the author conducting noise experiment with tape measure and ENVI PRO on April 10th, 2019.

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Rigging

The three factors that must be taken into consideration each time the magnetometer is

mounted upon the UAS include the overall protection of the ENVI PRO sensor, its orientation

with respect to magnetic North, and a proper sensor chord length. Roughly one inch of square-

cut foam is placed around the sensor and held in place by duct tape for protection. The sensors

North indicator was marked red duct tape (Figure 9a). This allows the operator to align the sensor

to the Earth’s ambient field before surveying. Beneath the foam, a general purpose nylon rope

is tied as a harness for the sensor (Figure 9b). The other side of the rope runs along the length of

the sensor’s chord and periodically guide loops are tied for the chord to pass through (Figure 9c).

A carabiner is tied to the end of the rope. The ENVI PRO’s console is attached to the UAS’s

mounting frame with four short ropes tied into loops passing through the eyelets of the device

and is lashed with carabiners. This was done to provide easier access to the ENVI PRO’s console

without unlashing the carabiners. A final rope is then rigged from these carabiners to construct

a four-point harness. This is where the sensor’s rope hangs from without the cord bearing weight

(Figure 9d). All metallic carabiners are placed near the console so that they do not influence

magnetic readings. The length of the cord with this setup is 2 m long which fulfills the 0.66 m

requirement for noise (Figure 9e).

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Figure 9a. ENVI PRO sensor wrapped with foam and North indicator marked with red.

Figure 9b. ENVI PRO sensor secured by tying a harness using nylon rope.

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Figure 9c. Guide loop tied to rope for sensor cord to pass through.

Figure 9d. Rope harness secured by carabiners to mounting frame. Sensor rope lashed to this harness using a single carabiner.

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Figure 9e. Sensor hanging on a frame to ensure weight is held by the rope and not the electrical cord.

2m

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Chapter 2 Testing The System Initial Test Flight

The newly assembled aeromagnetic survey system was granted access to the Nebraska

Intelligent MoBile Unmanned Systems (NIMBUS) lab’s test site for an initial test flight on May

10th, 2019. The test field is located near 84th St and Havelock Ave in Lincoln, NE (Figure 10). This

flight was conducted to ensure the ENVI PRO’s mounting method was viable, the system collects

reliable data, the sensor stays oriented to the North, and the motion of the M600 does not affect

data collection. A simple survey was designed on site consisting of three 130 m lines 10 m apart

(Figure 11).

The following operating procedures were established during this initial test flight.

1. The sensor will be placed outstretched and to the side of the M600 before taking off.

For landing, the M600 should be moved aside as soon as the sensor touches the

ground, so it is not damaged by UAS.

2. The ENVI PRO’s start button is pressed before the M600 is powered for the safety of

the user.

3. A 2 m/s flight speed is optimal for magnetic data collection at a sampling interval of 2

seconds (1 reading every 4 m).

4. A 7 m flight altitude puts the sensor at a clearance of 5 m. This is high enough to avoid

obstacles and low enough for accurate magnetic measurements.

5. A 10 second pause is programmed into the flight's mission after each turn at each

waypoint. This minimizes the swaying of the sensor after the abrupt movement.

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6. The aeromagnetic survey system must not be operated in inclement weather. This is

subjective as the system has not yet been tested for wind resistance and temperature

thresholds. Regardless, no surveys will be conducted in precipitation of any kind for

the safety of the user and the equipment.

Figure 10. Location of NIMBUS UAS test field near the corner of 84th St and Havelock Ave in Lincoln, NE traced in red.

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Total magnetic intensity (TMI) data taken from this survey was processed, and preliminary

data processing procedures were developed. Data processing will be covered fully in Chapter 3.

A magnetic anomaly map was compiled from the merged GPS and TMI data (Figure 11). This map

shows the changes in the magnetic anomaly across the survey area. There are no significant

variations in the magnetic field in the survey area or sporadic measurements (unlike records in

Figure 4a). No geologic structures are known in this survey area, so these results were expected.

The following conclusions were made. First, the system records reliable data because the

measurements are consistent between three adjacent lines. Second, the chosen operational

settings are appropriate for collecting aeromagnetic data (2 m/s speed, 7 m altitude, 2 second

sampling interval, and 2 m sensor distance from UAS). The procedures established during this

initial test were adopted for the major test survey over the Northern Bounding Fault. The author

obtained an FAA part 107 unmanned aircraft system pilot’s license after the conclusion of this

test so that a member of the Geophysics Team could begin learning UAS vehicle operations from

the NIMBUS lab pilot.

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Figure 11. Magnetic anomaly map from the initial test at 84th and Havelock site (Figure 10). The difference in anomaly is only ~3 nT indicating only minute variations in subsurface geology. The consistency of the measurements between adjacent lines indicate reliability of the system. No significant magnetic noise was observed, although no specific noise measurements were performed. The procedures used to generate this map were utilized for the next test survey over the NBF and are described in Chapter 3.

27

Primary Test Location and Geology

The aeromagnetic system was flown over the NBF of the MCRS as a final assessment of

its capabilities (Figure 12; Burberry et al., 2018). The survey location over this fault was roughly

1.33 km northeast of Venice, Nebraska. The complete legal location of the test site is Wann Wann

Quadrangle, Section 30, Township 15 North, Range 10 East, Douglas County, Nebraska, and the

GPS coordinates for the center of the survey area are latitude 41.242, longitude -96.337. The

landowner, Lyman-Richie Co., gave permission to the UNL Geophysics Team to access this land

on November 9th 2019. The land is used for corn farming which made aeromagnetic surveying

particularly appropriate due to the soft soil and cut corn stalks hindering walking surveys.

Figure 12a. Predicted geometry of the Midcontinent Rift System (labeled MRS in this figure) in Nebraska. Fault lines are presented as red. The survey target Northern Bounding Fault is labeled with a red arrow (Burberry et al., 2018)

28

Figure 12b. MCRS is apparent in magnetic anomaly map. (Burberry et al., 2018). Survey site is shown by white circle.

Figure 12c. Geographical location as related to Lincoln, NE. The nearest city, Venice, NE, is represented by a black circle. A blown up satellite image is presented on the right with the study area outlined by a red box. Coordinates are latitude 41.242, longitude -96.337.

Venice

200x200 m study area 1.33km from Venice

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The NBF of the MCRS was chosen as the target for testing of the aeromagnetic system

due to its distinct magnetic anomaly along fault lines (Figure 12b; Burberry et al., 2018). This

1.1 billion year old tectonic feature is comprised of igneous and sedimentary rocks. It stretches

3000 kilometers across the central United States and is exposed at Lake Superior (Stein et al.,

2016). Flood basalts and gabbros make up the majority of the Proterozoic igneous rocks covered

by Phanerozoic strata (Van Schmus and Hinze, 1985). The MCRS is a failed rift system that formed

from tectonic extension forces in the middle of the paleocontinent Laurentia (Figure 13). The

Midcontinent rifting was not successful in splitting the continent and forming an oceanic crust.

The traditional hypothesis is regional compression in the later stages of the Grenville orogeny

(1.3-0.98Ga) terminated the extension (Gordon and Hempton, 1986; Cannon, 1994). However,

new age detrital zircon dating has revealed that most of this compression occurred long after the

MCRS extension was halted (Stein et al., 2014; Stein et al., 2016). A revised hypothesis has been

proposed by Stein et al., 2014, and matches the rift failure age (1.1 Ga). The initiation of the

spreading center at the eastern coast of Laurentia caused compressional stresses in the middle

of the continent and ultimately caused the MCRS to fail.

30

Figure 13. The spreading between the paleocontinents Amazonia and Laurentia are hypothesized to have caused the compressional stresses that halted the MCRS (Stein et al., 2014). The Grenville Front is the westward extent of orogeny attributed deformation which occurred after the separation of the plates (Stein et al., 2017). The evidence of Amazonia movement is observed in the rocks of the present day South American plate. Rift volcanism is recorded in Nova Brasilândia rocks (Teixeira et al., 2010). Amazonia left lateral movement is recorded by the Ji-Paraná shear zone (Tohver et al., 2006). And, rifting associated with the separation of the two plates is recorded by the Haunchaca and Rincón del Tigre igneous rocks that have been dated to 1.1 Ga (Ernst et al., 2013)

S

31

Variations in subsurface geology along the NBF of the MCRS are associated with the

contrast in magnetic susceptibility of igneous and sedimentary rocks. Low magnetic sedimentary

rocks are juxtaposed to the highly magnetic igneous rock of the MCRS. Figure 14 from Burberry

et al. (2015) shows the geometry of the MCRS and these lateral variations. The difference in

magnetic susceptibility makes this fault a good target for a test of the aeromagnetic surveying

system.

Figure 14a. Location of MCRS, the NBF, the south bounding Union Fault (UF). Red line shows the cross section profile for Figure 14b.

32

Figure 14b. Cross-section showing sedimentary layers and MCRS igneous rock (Precambrian

basement). Lateral variation across the fault lines represents contrast in magnetic

properties (red line marks the fault selected for the aeromagnetic survey).

N S

33

Northern Bounding Fault Survey

Permission was granted by Lyman-Richey Co. for access of a 200x200 m total area for use

(Figure 12c). Planning for the survey required careful design of flight paths. A preliminary sketch

is presented in Figure 15a. Two separate flight missions were planned to cover as much of that

area as possible (Figure 15b). One flight intended to acquire data perpendicular to the fault line

with diagonal profiles connecting each waypoint. Flying perpendicular provides the best data to

map the fault. The other flight consisted of several lines parallel to the fault strike with diagonal

lines connecting each waypoint. A parallel flight would fill in gaps in magnetic data and allows

for examining the accuracy of recorded data. The lines from the second flight intersect the lines

from the first flight and the accuracy and repeatability could be examined from these crossing

points. These two flights were designed in Google Earth Pro prior to departing for the survey

site, where the waypoints were converted into decimal degrees for input into Ground Station

Pro.

Figure 15a. Preliminary sketch used to devise the NBF survey plan. Waypoints are numbered.

34

Figure 15b. Survey plan devised in Google Earth Pro prior to departing for the NBF. Waypoints here were converted into decimal degrees in Ground Station Pro app. Three lines were planned per flight. Flight 1: Red Flight 2: Blue

Fault

35

On November 9th, 2019 the survey over the Northern Bounding Fault was conducted

(Figure 16)(Jacobson and Filina, 2020a). First, the waypoints were inputted into the Ground

Station Pro application. Next, the M600 was placed onto a solid takeoff point near the mission

start location, and the ENVI PRO was attached to the mounting frame. It is important to set up

the timestamp on the ENVI PRO to the correct Coordinated Universal Time (UTC) prior to the

flight. Then, the device was turned on to begin collecting magnetic measurements. Finally, the

drone was powered on, the pilot took off, and the mission in Ground Station Pro was initiated.

The flight parameters from the initial test were sustained with a 2 m/s flight speed and a 7 m

flight altitude for both flights conducted. The improvement in the operating procedure that was

discovered from the previous survey, was the 10 second pause after each programmed turn. This

is because the motion of stopping and turning UAS triggers the sensor to sway. A 10 second

pause after this turn allows the sensor to stabilize before moving forward for the next line in the

mission. Once the mission is complete, the pilot takes control of the UAS for landing with the

sensor touching down first and then landing the UAS to the side. The UAS must be powered off

before stopping the ENVI PRO. In between the two flights, the intelligent flight batteries were

replaced, and the line number for the magnetic data was set appropriately. Both missions were

carried out successfully with flight one lasting ~12.5 minutes and flight two of ~18 minutes.

Appendix C is a simple workflow that summarizes the operating procedures that have been

devised for aeromagnetic surveys with the M600/ENVI PRO platform.

36

Figure 16. Photos of author and NIMBUS Lab pilot conducting aeromagnetic survey of the NBF of the MCRS. Top Left: Rigging and powering the ENVI PRO Top Right: Pilot preparing for takeoff with sensor laying with cord outstretched. Bottom: Pilot initiating Ground Station Pro mission after takeoff.

37

Chapter 3 Working With Data

Processing Raw Data

After conducting the NBF survey, raw unprocessed data collected by both the

magnetometer and the UAS were first downloaded. The ENVI PRO uses a universal serial bus

(USB) cable to transfer magnetic readings as digital data in an application called Data Logger

(Figure 17). Data is outputted as a .txt file separating TMI readings and survey parameters such

as line number, noise values, and timestamps into columns. The settings on the ENVI PRO must

be properly set for data output. The bits per second sent value is adjustable by changing the

BAUD number on the “OUTPUT” screen of ENVI PRO’s console. The BAUD number must match

on the console and in Data Logger to output data. For standard operating procedures, this

number is left at the default value 9600 bits per second. In addition, there are three different

output formats on the magnetometer’s console labeled xyz, xyz+, and xyz++. The xyz++ is the

most descriptive format and outputs a heading in the resultant .txt document. This setting was

chosen for standard operating procedures because time, date, and column labels are included in

this heading. An additional heading also separates each line of magnetic readings allowing for

easy processing. An example of this .txt file is given in Figure 18.

The ENVI PRO .txt file was inputted into Microsoft Excel where a time in seconds column

and a magnetic anomaly column was set aside on a new worksheet. The ambient field for this

location and time was 53,272 nT and was found through the online calculator at

http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml (Figure 19).

Szopinski (2019) found that this online calculator from the British Geological Survey gives a better

http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml

38

match in magnetic anomaly compared with published USGS data than other calculators. The

ambient field value was subtracted from the TMI to calculate the magnetic anomaly. The time

in seconds column was drafted by converting the time in decimal hours data into time in seconds

(Figure 20).

Figure 17. Data Logger application. The COM ports are the USB ports on a computer. If there is more than one, several options will appear and the correct one will have to be selected. The Baudrate number will have to match the BAUD number on the ENVI PRO’s output screen (default number is 9600 bits per second).

39

Figure 19. Ambient field value of 53,272 nT was found via online calculator provided by the British Geological Survey (www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml).

Figure 18. Example of ENVI PRO data once downloaded as a .txt file. The GPS coordinates are outlined in green (No values without onboard GPS) TMI is outlined in blue The noise value recorded by magnetometer is outlined in yellow UTC timestamp in decimal hours is outlined in red (hours from start of the day) And Uncor, a value used in gradiometer surveys, is outlined in purple (no values without using gradiometer function) This is the survey data processed in Microsoft Excel.

http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml

40

Figure 20. Resultant Excel columns of processed ENVI PRO data. Time in seconds is calculated by using the truncate function in Excel on the time in decimal days raw data to convert it to time in hours. This is then reduced to seconds. For the NBF fault survey the UTC time was not set on the magnetometer before taking off. Thus, the magnetometer’s timestamp data was 8336 s ahead. This was subtracted from the day in seconds value and a full day of seconds (86400) was added (~0100 hours converted to ~2300 hours in UTC). The anomaly value was calculated by subtracting the ambient field from the TMI data.

41

The next step in data processing is to convert raw data from the M600 into Excel columns.

Ground Station Pro automatically uploads all flight data onto an online database at

https://app.airdata.com/. It shows both missions and their corresponding parameters

(Figure 21). From this database, the comma separated value files are downloaded and opened in

Excel. This spreadsheet has 32 columns of different flight parameters that were recorded during

the survey every 0.1 s. The columns used for data processing are the UTC timestamp and date

and the GPS coordinates (Figure 22). The UAS recorded UTC timestamp is also converted into

time in seconds, this time starting from an hour/minute/second format. These columns are

copied into a new worksheet to prepare for the next step. Both ENVI PRO and UAS Excel

worksheets are saved as .txt files.

https://app.airdata.com/

42

Figure 21. The two separate flights as they appear in http://app.airdata.com. Comma separated value files of the data from the flights can be downloaded using the “CSV” button at the bottom.

http://app.airdata.com/

43

Figure 22a. UAS raw data. The first 4 columns of UAS data as they appear in Excel. Data is taken every 0.1 s (column A). Information used for data analysis is in column B, C, and D (UTC, latitude, and longitude respectively).

Figure 22b. New worksheet organizing UAS data into time in seconds, latitude, and longitude.

44

All of the data (both magnetometer and UAS) recorded before the start of the mission is

not included in the .txt files to eliminate magnetic readings taken during the setup and the takeoff

prior to the mission (Figure 23).

The reason the two datasets are organized as shown in Figures 20 and 22b is that the ENVI

PRO does not have an onboard GPS, thus the M600’s GPS needs to be utilized. A code was written

in MATLAB that uses the UTC time of each dataset to merge them into one with a time, location,

and magnetic anomaly (see Appendix D). The MATLAB program took .txt files from the columns

in Excel (Figures 20 and 22b) and generates a .txt file with merged data (Figure 24).

ENVI PRO M600

Combined Data

Figure 24. MATLAB program’s work to combine the two datasets by using the time in seconds taken by each device (Please note the numbers from Figures 20 and 22b are different from this file).

45

The resultant datasets for two flights were combined and imported into ArcMap 10.6.1

(GIS) by adding them as x,y,z data with longitude assigned as x, latitude assigned as y, and

magnetic anomaly assigned at the z component. Further data analysis was done in GIS

(Figure 25).

Figure 23. Excel Column showing where data was omitted from .txt files to eliminate pre-survey valueless TMI readings that will skew analysis. These can be Identified by the UAS’s status messages (Excel column AR).

Figure 25. Magnetic anomaly data points from the NBF survey as viewed in GIS (green). 200x200m survey area outlined in yellow. NBF shown in red.

46

Data Analysis

Each point is expanded by 5 m using the “Buffer” tool in GIS. The “Intersect”

geoprocessing tool was then used to compare the magnetic readings of the two separate flights

where they crossed paths (Figure 26a). A shapefile was generated showing 21 points where

magnetic anomaly data overlapped (Figure 26b). The readings were compared to examine the

accuracy of the magnetic surveying system (Jacobson and Filina, 2020b). The dataset table

produced in GIS was imported into Microsoft Excel (Figure 26c). Differences between anomaly

readings at each point were computed and then the average difference was calculated. One

outlier of over 5 nT was noted. The average difference in magnetic anomaly was 2.1 nT for all

cross points and 1.9 nT with the outlier removed.

Figure 26a. GIS shapefile generated using the “Intersect” tool. Green: Flight one (Buffered) Yellow: Flight two (Buffered) Purple: Intersecting points

47

Figure 26b. Table generated from “Intersect” shapefile tool in GIS. Magnetic anomaly values are highlighted.

Figure 26c. Excel file showing the two magnetic anomalies at crossing points and the difference between them. Two averages differences were calculated. One for the whole table and one omitting the outlier value in cell C7, 2.1 and 1.9 respectively.

48

A magnetic anomaly map was composed in GIS from the flight data points using the

“Kriging” tool (Figure 27). This map shows the aeromagnetic data, start points and flight paths

of the different missions, and the published NBF from Burberry et al. (2018). Another map was

composed using USGS data compiled from Sweeny and Hill (2005) for direct comparison with

published data (Figure 28). This dataset was compiled from three regional airplane-based

magnetic surveys collected in the 1960s. The spacing between data points is 500 m. Since the

NBF survey study area was only 200x200 m, the USGS data is heavily interpolated to show the

magnetic anomaly within the boundaries. Despite these limitations, there are two comparisons

that can be made. First, both magnetic anomalies show a similar trend in the field decreasing

from the northwest to southeast. Second, the magnetic anomalies are offset in their values by

roughly ~30 nT. This may be related to diurnal variations not taken into account during the

survey.

49

Figure 27. Magnetic anomaly map with flight paths, start points, and the published NBF location (Burberry et al., 2018)

Figure 28. USGS aeromagnetic data compiled by Sweeney and Hill (2005) interpolated across survey area. Data points from this survey are widely spaced compared to the UAS based survey. This magnetic anomaly trends similarly but is ~30 nT offset (USGS anomaly is higher). A single data point is shown as a brown dot.

Venice,

Venice,

Published

Fault

50

The UAS based survey suggests a different trend for the NBF fault within the study area

(Figure 29). This trend is a result of a much more detailed survey. The aeromagnetic survey using

a UAS offers many more magnetic readings in the 200x200 m area and is more descriptive. Thus,

the fault shown in Figure 29 is interpreted from the high-resolution magnetic data. More

surveying in adjacent areas is necessary to investigate this fault further.

Figure 29. Magnetic anomaly map from the UAS based aeromagnetic survey system showing the NBF’s trend as in appears in the magnetic data.

Interpreted Fault

Venice,

51

Conclusion

The successful development of a low-cost aeromagnetic surveying system required

fulfilling three primary objectives. First, determining optimal UAS flight settings for the ENVI PRO

magnetometer. Second, mounting the ENVI PRO in a manner that reduces magnetic noise to

negligible levels. Third, conducting a successful survey over a known geologic structure and

identifying the structure in magnetic data.

The first objective of the study was met by finding optimal settings in the ENVI PRO user

manual (ENVI PRO Manual, 2009) and by conducting walking tests to collect TMI data. The

advanced mode was determined to be the optimal setting for geological fieldwork because it

gave the user the most control over survey settings. WALKMAG mode was found to be the only

setting that allowed for continuous TMI data collection. These settings were confirmed and

became standard in the walking trails at Mable Lee Field where the different sampling rates were

tested. One measurement every two seconds was determined to be the optimal sampling

interval for data accuracy with moderate movement (1.5 m/s).

Mounting the ENVI PRO to the M600 required defining the optimal sensor distance to

minimize magnetic interference from the powered UAS and using the proper method of rigging.

The sensor distance was found by powering the drone so the internal electric currents produced

electromagnetic fields. The magnetic noise due to these fields was acceptable at distances

greater than 0.66 m from the UAS. A 2 m separation from the sensor to UAS became the standard

to ensure minimal vehicle influence and protect the sensor during taking off and landing. As for

rigging the ENVI PRO, the sensor was wrapped in foam for protection in case of a rough landing.

52

Nylon rope tied as a harness and bear the weight of the hanging sensor and the console of the

ENVI PRO. Metal carabiners are used to lash the end of the sensor’s rope to the console’s harness

and the ENVI-Pro to the mounting frame of the UAS. No carabiners were placed near the sensor

itself so that their metallic elements would not cause any noise. This objective is also determined

to be successful.

Two separate field tests were conducted. The objectives for the first one were to test the

airborne surveying system and to determine optimal flight settings. The second test was

performed over a known geological structure. The structure selected for the trail was the NBF of

the MCRS near Venice, NE due to known high variations of the magnetic field over the structure.

Fieldwork was carried out on November 9th, 2019 in a 200x200 m area above the fault. Two

separate flight missions were flown successfully, one perpendicular to the structure and the

other one parallel. Analysis of the recorded data revealed a 1.9 nT average difference in magnetic

readings in the cross points of two flights. A magnetic anomaly map was composed and

compared to USGS’s published aeromagnetic data (Sweeney and Hill, 2005). Both fields have a

similar trend where the anomaly decreases from the northwest to the southeast of the study

area. However, the UAS aeromagnetic data was offset ~30 nT lower than the previously published

data. The NBF interpreted from UAS based aeromagnetic data suggests a different trend than

previously published that requires further investigation.

The third objective is determined to be successful. The ~30 nT difference in magnetic

anomaly from USGS’s published aeromagnetic regional map is a large disagreement most likely

related to diurnal variations that were ignored in the UAS survey. On the other hand, the surveys

compiled by Sweeney and Hill (2005) were flown in the 1960s on airplanes moving much faster

53

and at a higher altitude than the UAS. These produced much less detailed data meant for regional

exploration and only one data point from the published grid was inside the study area. A follow

up walking survey with the ENVI-Pro would help to study the observed ~30 nT offset. The

disagreement in the published trend of the fault line also requires additional aeromagnetic

surveys. The NBF being a segmented fault system would explain this disagreement. Expanding

the survey area to search for adjacent fault segments would test this hypothesis. However, due

to the COVID-19 pandemic in spring 2020, no further fieldwork was permitted.

As a result of this project, the UAS based aeromagnetic surveying system was assembled

and successfully tested. The author composed detailed and comprehensive operating procedures

to operate the system. Directions for survey design, field preparation, and data processing

workflow are also provided. All of these materials will enable more efficient future fieldwork

than the pioneering work done by the author.

54

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Retrieved from https://app.airdata.com/flight/last

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Nemaha Tectonic Zone and Midcontinent Rift System, SE Nebraska and N Kansas: The

Mountain Geologist, v. 52, n. 4. p. 47-73.

3. Burberry, C., Swiatlowski, J., Searls, M., and Filina, I., 2018, Joint and Lineament Patterns

across the Midcontinent Indicate Repeated Reactivation of Basement-Involved Faults:

Geosciences, v. 8, p. 215, doi: 10.3390/geosciences8060215.

4. Cannon, W.F., 1994, Closing of the Midcontinent rift—A far-field effect of Grenvillian

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7613(1994)0222.3.CO;2.

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1951(86)90076-4

6. Cunningham, M., Samson, C., Wood, A., and Cook, I., 2018, Aeromagnetic Surveying with a

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in Geosciences, p. 5-18, doi: 10.1007/978-3-030-03171-8_2.

7. DJI GS Pro - Manage Drone Operations on Your iPad - DJI DJI Official. Retreived from

https://www.dji.com/ground-station-pro

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8. ENVI PRO Operation Manual, 2nd ed, Scintrex Limited, Concord, ON, 2009 9. Ernst, R.E., Pereira, E., Hamilton, M.A., Pisarevsky, S.A., Rodriques, J., Tassinari, C.C., Teixeira,

W., and Van-Dunem, V., 2013, Mesoproterozoic intraplate magmatic 'barcode' record of the

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10. Filina, I., Guthrie, K., Searls, M., and Burberry, C., 2018, Seismicity in Nebraska and adjacent

states: The historical perspective and current trends: The Mountain Geologist, v. 55, p. 217-

229, doi: 10.31582/rmag.mg.55.4.217.

11. Jacobson, E., Filina, I., 2020a, Mapping subsurface fault system using a drone-based

magnetic field surveying system, Proceedings of 140th annual meeting of Nebraska

Academy of Sciences, p. 78

12. Jacobson, E., Filina, I., 2020b, Testing a drone-based magnetic field surveying system, Poster

presented at: UCARE Research Products 2020, 2020 April 14,

https://digitalcommons.unl.edu/ucareresearch/

13. Jacobson, E., I. Filina, 2019, Developing a drone-based magnetic field surveying system,

Proceedings of 139th annual meeting of Nebraska Academy of Sciences, p. 115

14. Lillie, R.J., 1999, Whole earth geophysics: an introductory textbook for geologists and

geophysicists: Upper Saddle River, NJ, Prentice Hall.

15. MagArrow UAS-Enabled Magnetometer Geometrics. Retrieved from

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16. Matrice 600 pro. Retrieved from https://www.dji.com/matrice600-pro

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17. Matrice 600 pro User Manual, 1st ed, DJI, 2018

18. Stein, C.A., Stein, S., Elling, R., Keller, G.R., and Kley, J., 2017, is the “Grenville Front” in the

central United States really the Midcontinent Rift?: GSA Today, p. 4-10, doi:

10.1130/gsatg357a.1.

19. Stein, C. A., Stein, S., Merino, M., Keller, G. R., Flesch, L. M., Jurdy, D. M. 2014. Was the

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1465– 1470, doi:10.1002/2013GL059176.

20. Sweeney, R.E., Hill, P.L. 2005. Nebraska, Kansas, and Oklahoma Aeromagnetic and Gravity

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21. Teixeira, W., D’Agrella-Filho, M.S., Hamilton, M.A., Ernst, R.E., Girardi, V.A., Mazzucchelli,

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the Columbia supercontinent: Lithos, v. 174, p. 157–174,

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22. Tohver, E., van der Pluijm, B.A., van der Voo, R., Rizzotto, R.G., and Scandolara, J.E., 2002,

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23. Unlv Faculty., n.d. Magnetism: Notes, Proton Precession Magnetometer. Retrieved from

https://pburnley.faculty.unlv.edu/GEOL442_642/MAG/NOTES/MagNotes23proton.html

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57

Appendix A: Workflow for ENVI-MAG WALKMAG and UAS Operation

1) Startup

a) Load battery inside of back plate if not already done so

b) Cold boot

(1) Press ON/OFF button at same time as AUX/LCD button while the power is OFF

(2) Press 9 button to select YES

(3) This will wipe memory and reset the settings

c) To select magnetometer applications

(1) Press ON/OFF and SETUP button at same time while device is powered OFF

(2) Press 1 for MAG only

(3) Scroll down using +/- buttons and select #6: MINERAL EXPLORATION

(4) You will then be at the MEASURE/START screen

2) Setup

a) Press INFO (#7) button to check date and time from MEASURE/START screen

i) Change DATE AND TIME to correct UTC time using the ARROWS, NEXT, and ENTER

buttons

ii) Press ESCAPE to return to the MEASURE/START screen

b) Press SETUP button

c) Scroll using ARROWS, NEXT, and ENTER buttons to

i) Select YES in CYCLE REPEAT

ii) Select MAG SETUP and press ENTER

(1) Change DURATION to 2 seconds

(2) Change TUNE FIELD to AMBIENT FIELD

(3) Make sure AUTO-RECORD is at YES and MODE is on t-fld

(4) Do not mess with other parameters

(5) Press ESCAPE to return to the MEASURE/START screen

3) Survey

a) Make sure sensor is connected and orientated NORTH

b) Press the START/STOP/CLEAR button on MEASURE/START screen to begin taking

measurements

c) Walk until you have completed your line and then press START/STOP/CLEAR

d) Press ESCAPE to return to MEASURE/START screen

i) To change lines and to add separation

(1) Press NEXT on MEASURE/START screen

MEASURE/START screen

58

(2) Move cursor to SEP to add your line separation measurement

(3) Move cursor to LINE to change the survey line for next measurement

e) Repeat until you have completed your survey

4) Output

a) Connect data output cable and plug into USB port on computer (know which COM port

you use)

b) Open DATALOGGER application in BOX>2019_Field_Methods>Erik_Jacobson>Logs

c) On magnetometer

(1) Press AUX/LCD

(2) Press 1 for OUTPUT

(3) Make sure BAUD number matches DataLogger

d) On datalogger

(1) Make sure you have selected the right COM port for your cord

(2) Press START LOGGING

e) On magnetometer

(1) Press NEXT twice and then change FMT to XYZ++

(2) Press START/STOP/CLEAR on output screen

(a) All data recorded should be selected

f) Data logger should receive data then turn it into a text file with a different header for

each LINE separating the data.

OUTPUT screen

59

Some notes on this workflow are presented here:

1) The “Mag Only” application is used since only one sensor is mounted (not enough

equipment for a gradiometer survey).

2) “Mineral Exploration” is the best application for find deep geologic structures

3) “Cycle Repeat” causes the magnetometer to take constant readings without pressing the

start button at each point

4) Changing “Duration” to 2 seconds will cause the magnetometer to take a reading every 2

seconds when “Cycle Repeat” is selected.

5) “Auto-Record” is changed to “Yes” so that every reading is kept for data output and the

“Record” button does not have to be pressed.

6) The “Tune Field” setting will always need to be changed to reflect the Earth’s ambient

magnetic field at the location that is surveyed, at least within 1000 nT. Can be found at

http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml

7) “Datalogger” is a computer application that converts the data from the ENVI PRO into a .txt

file. Changing the “FMT” (format) to “XYZ++” in the output screen puts a new heading after

each separate line’s data in the .txt file.

http://www.geomag.bgs.ac.uk/data_service/models_compass/igrf_form.shtml

60

Appendix B: Aeromagnetic Survey Packing List

A packing list for the field has been compiled due to author forgetting a chord that connects the

iPad to the UAS controller.

Drone

o Drone

o 3 sets fully charged batteries

o Controller

o iPad

o Controller-iPad cord

o Take off board

o Battery charger

o Battery charger cord

Magnetometer

o Console

o Sensor

o Rigging

o Spare rigging

o Note taking equipment

o Measuring tape

o Marking flags

61

Appendix C: UAS Based Aeromagnetic Survey Workflow

1. Pre-Survey

a. Create and plot mission into GROUND STATION PRO app

i. Mission Waypoints from Google Earth Pro (decimal degrees)

ii. 10 second pause at each waypoint

iii. Speed of drone

iv. Altitude of drone

b. Charge every battery to full

c. Assemble packing list

2. Field Survey

a. Set up drone in level location

b. Raise, spread, and uncover propellers

c. Mount magnetometer

d. Insert all 6 batteries

e. Attach and start magnetometer

f. Power drone

i. Press button on any battery once then press and hold

g. Pilot takes off and orients sensor North

h. Pilot starts automated mission

i. Drone flies mission

j. Pilot takes over and lands drone

k. Power off drone

i. Press button on any battery once then press and hold

l. Stop magnetometer

m. Repeat as needed

i. Make sure to change batteries and line # on magnetometer.

62

63

Appendix D: MATLAB CODE

function drone_mag_merge;

%fuction to merge data from drone (time in sec, lat, long) with data from

%magnetometer (time in sec, mag_reading (T in nT))

load('magflight1_Nov9_2019', '-ascii');

load('droneflight1_Nov9_2019', '-ascii');

t1=magflight1_Nov9_2019(:,1);

T=magflight1_Nov9_2019(:,2);

t2=droneflight1_Nov9_2019(1:10:end,1);

lat=droneflight1_Nov9_2019(1:10:end,2);

lon=droneflight1_Nov9_2019(1:10:end,3);

T_drone=interp1(t1,T, t2, 'linear');

out=[t2,lat, lon,T_drone];

save('mag_drone_flight1_Nov9th_2019.txt', 'out','-ascii');

end

64

Some notes on this code is presented here:

“magflight1_Nov9_2019”in the 4th line is the ENVI PRO’s timestamp and magnetic

reading .txt file (Figures 20 and 24)

“droneflight1_Nov9_2019”in the 5th line is the M600’s timestamp and coordinates .txt

file (Figures 22b and 24)

o The .txt file name and the name in these “load” lines must match

The merged .txt file is named “mag_drone_flight1_Nov9th_2019.txt” in line 13 and can

be renamed within the code

The merged .txt file’s destination is the folder where the files to be merged are located.

The code is executed from this folder.

65

Appendix E: Lessons Learned

Some lessons learned while working on this research are presented here:

Print these files for use as checklists and study before operation

o Equipment operation workflow (Appendix A)

o Packing list (Appendix B)

o Survey operations (Appendix C)

Design the missions and input the waypoints in Ground Station Pro prior to leaving to

conduct the field work

o To find waypoints in decimal degrees (the format Ground Station Pro uses) in

Google Earth Pro go to Tools>Options

Place mission start points near where the team will be located (not across the field)

Make sure ENVI PRO’s UTC timestamp is set to match the GPSs on the M600 prior to

beginning the survey

Completely review and understand ENVI PRO manual (2009) and M600 manual (2018)

Set aside at least twice the time that is thought that is needed for a survey