Rodriguez, R., D. Jenkins, J.K. Leary and B.V. Mahnken. 2016. Herbicide Ballistic Technology:
Spatial Tracking Analysis of Operations Characterizing Performance of Target Treatment.
Trans ASABE. Transactions of the ASABE. 59(3): 803-809.
Rodriguez, R., D. Jenkins, J.K. Leary. 2015. Design and Validation of a GPS Logger System for
Recording Aerial-Deployed Herbicide Ballistic Technology Operations. IEEE Sensors. 15:
2078-2086.
Leary, J.K., B. Mahnken, L. Cox, A. Radford, J. Yanagida, T. Penniman, D. Duffy and J. Gooding.
2014. Reducing Nascent Miconia (Miconia calvescens DC) Patches through Accelerated
Interventions Utilizing Herbicide Ballistic Technology (HBT). Inv. Plant Sci. Mgmt. 7 (1)164-175. DOI: 10.1614/IPSM-D-13-00059.1 Awarded 2015 Outstanding Paper for IPSM
Leary, J.K., J. Gooding, J. Chapman, B. Mahnkan, A. Radford, L. Cox, 2013. Calibration of an
Herbicide Ballistic Technology (HBT) Helicopter Platform Targeting Miconia (Miconia
calvescens DC) in Hawaii. Inv. Plant Sci. Mgmt. 6(2) 292-303. DOI: 10.1614/IPSM-D-1200026.1 (with press release; see popular media)

HERBICIDE BALLISTIC TECHNOLOGY: SPATIAL TRACKINGANALYSIS OF OPERATIONS CHARACTERIZINGPERFORMANCE OF TARGET TREATMENT
R. Rodriguez III, J. J. K. Leary, D. M. Jenkins, B. V. Mahnken

ABSTRACT. Since 2012, the Herbicide Ballistic Technology (HBT) platform has been deployed in helicopter operations
with a mission to eliminate nascent populations of the invasive plant species miconia (Miconia calvescens DC), which isspreading across the East Maui Watershed in Hawaii. The HBT platform is a refined pesticide application system thatpneumatically delivers encapsulated herbicide projectiles (i.e., paintballs) from a long range (up to ~30 m) and varying
attitude. This onboard system provides accurate, effective treatment of individual plant targets occupying remote, inaccessible portions of the forested landscape. Statistics of operational performance are acquired through GIS analyses of recorded GPS data assigned to treated plant targets. Recently, we have developed a telemetry system for HBT applications(HBT-TS) to enhance the attribute data of target treatments. The HBT-TS integrates a hardware sensor with the electropneumatic marker that is actuated by the trigger to generate time-stamped, geo-referenced attribute data, including target
assignment, azimuth, tilt, and range determined from the applicator position, for every projectile discharged. With target
assignments, the HBT-TS records the estimated dose applied to each target. Furthermore, the time stamps show that theactual time to administer projectiles (i.e., target treatment) is a minor component of the total time on target. By tracking
the orientation and distance of the discharged projectile, we can calculate a precise offset target location relative to theapplicator position and provide a more accurate interpretation of the herbicide use rate (g acid equivalent ha-1) based on
the known amount of herbicide contained in each projectile and the final placement on the landscape. We acknowledge
the challenges of GPS inaccuracies while recording in a dynamic environment (i.e., a moving platform in extreme topography), albeit with increased precision. Regardless, the current state of the HBT-TS technology enhances operational intelligence relevant to landscape-scale invasive species management.
Keywords. Aerial application, GIS, GPS, Miconia calvescens DC, Remote sensing, Telemetry.

T

he Hawaiian archipelago is the most isolatedgroup of islands on Earth, resulting in the evolution of endemic, highly specialized biotic communities (Carlquist, 1970; Mueller-Dombois etal., 1981; Stone and Scott, 1985). Currently, approximately
1100 endemic plant species and 4600 introduced exotic
species have been catalogged, of which about 800 are considered invasive (Stone and Scott, 1985). These invasiveplant incursions are threatening the ecological integrity andfunction of Hawaii’s forested watersheds (Cox, 1999; Lindenmayer et al., 2000; Loope and Kraus, 2009; Loope etal., 2004; Mooney and Drake, 1986; Stone et al., 1992).

Submitted for review in August 2015 as manuscript number ITSC
11474; approved for publication by the Information, Technology, Sensors,& Control Systems Community of ASABE in January 2016.
The authors are Roberto Rodriguez III, ASABE Member, Graduate
Student, Department of Biosciences and Bioengineering, University of
Hawaii at Manoa, Honolulu, Hawaii; James J. K. Leary, Extension
Specialist, Department of Natural Resources and Environmental
Management, University of Hawaii at Manoa, Kula, Hawaii; Daniel M.
Jenkins, ASABE Member, Professor, Department of Biosciences andBioengineering, University of Hawaii at Manoa, Honolulu, Hawaii;
Brooke V. Mahnken, GIS Specialist, Maui Invasive Species Committee,
Makawao, Hawaii. Corresponding author: Roberto Rodriguez III, 218
Agricultural Science Building, 1955 East-West Road, Honolulu, HI
96822; phone: 727-415-6712; e-mail: roberto6@hawaii.edu.

One of the most significant plant invasions in Hawaii is
miconia (Miconia calvescens DC) in the East Maui Watershed (EMW). The EMW is 55,000 ha of forested landscapeon the northeastern slope of Haleakala volcano. Miconia
was introduced as an ornamental nursery stock plant in
Hana in 1970. Today, the core infestation is approaching1000 ha surrounding Hana, with small nascent populations
spread across 20,000 ha of the EMW. Interventions onthese incipient outlier populations are critical to maintaining an effective containment strategy for protecting themost intact endemic forest areas. The extreme topography
and remote location of the EMW are major impediments toeffective intervention with ground-based operations(Kueffer and Loope, 2009). Herbicide Ballistic Technology(HBT) is a novel pesticide application technology (registered as a 24(c) Special Local Need pesticide in Hawaii)that addresses these challenges with a capability to effectively treat individual plant targets with long-range accuracy and flexible attitude from a helicopter, while conducting
surveillance operations (Leary et al., 2014).
Since 2012, HBT interventions have eliminated over
14,000 incipient miconia targets, as recorded by GPS fromthe applicator position on the aircraft. However, with aneffective range of ~30 m, these coordinates are not the actual target locations. Furthermore, the herbicide dose has

Transactions of the ASABE
Vol. 59(3): 803-809© 2016 American Society of Agricultural and Biological Engineers ISSN 2151-0032 DOI 10.13031/trans.59.11474

803

been calculated as a composite average of the total estimated projectile inventory discharged to the total number oftargets recorded. To enhance analyses of operations, a telemetry system was developed with sensor hardware integrated into the electro-pneumatic propulsion system (i.e.,
paintball marker) in which the data acquisition sequence isactuated by the trigger pull, populating a data matrix withthe azimuth, tilt, target ID, time stamp, and geodetic coordinates for each projectile discharged (Rodriguez et al.,2015). In this article, we report on a second-phase iterationof the telemetry system for HBT applications (HBT-TS)
with a laser range finder augmenting the sensor hardware,
which introduces the capability to geometrically calculate
the offset location of the target from the applicator position.
This further increases the resolution of the calculated metrics pertinent to the operation, including spatial statistics
using the distance to the target to estimate the final positionof each projectile and the herbicide use rate.
In 2013, we developed our first iteration of a fully operational HBT-TS that could perform basic functions inrecording geo-referenced locations with time stamps of allactions specific to an HBT operation (Rodriguez et al.,2015). The telemetry hardware consists of a printed circuitboard populated with several sensors, including barometricaltimeter, gyroscope, magnetic compass, and triple-axis
accelerometer that transmit data via Bluetooth to a devoted
software application written in Android open source code.
We have since initiated phase II development of the HBTTS with incorporation of a laser range finder (LRF) capableof quantifying the distance to target treatment (up to 40 m).
As described by Rodriguez et al. (2015), the HBT-TS sensor device is mounted parallel to the barrel on the side picatinny rail, a series of extrusions with T-shaped crosssections used to mount accessories onto a firearm or similar
device, of the electro-pneumatic marker (BT TM7, Kee
Action Sports LLC, Sewell, N.J.), with an interrupt-enabled
I/O pin connected to the open-drain contact controlling thefiring-solenoid current. When this signal is observed to go

to ground (i.e., projectile is discharged), the system records
the current time along with the most current sensor data
attributed to the projectile and target (fig. 1).

MATERIALS AND METHODS
A total of five aerial miconia interventions were conducted in February and March of 2015 for testing the secondgeneration HBT-TS with LRF in a dynamic operational setting. The orientation sensors on the device were calibratedusing a compass and clinometer (360PC/360R Suunto Tandem, Amer Sports Corp., Helsinki, Finland) prior to the first
operation of each day. The barometric altimeter was calibrated before each operation using the known elevation of theheliport or landing zone. All operations were conducted using a Hughes 500D helicopter with the applicator positioned
port side behind the pilot, so the pilot and applicator shared
the field of view for target detection and engagement. Upon
detection, the applicator pressed the target acquisition button(fig. 1), establishing a unique target ID to be assigned to all
subsequent projectiles discharged until the next acquisition.
In the meantime, the pilot approached the target for a clear
line of sight within effective range and held the position
while the applicator administered the projectile dose to thetarget. In these operations, all projectiles (x = 6845) werecorrectly assigned to targets (n = 365).
The distribution of the applicator GPS position and calculated offset coordinates for each target were calculatedusing the circular map accuracy standard (CMAS) andspherical accuracy standard (SAS). The CMAS is the magnitude of the radius of the smallest circle, in the plane tangent to the Earth at the mean location corresponding tolatitude and longitude, containing 90% of the recorded positions (USBB, 1947). The SAS is the magnitude of theradius of the smallest sphere containing 90% of the recorded positions (Greenwalt, 1962). Assuming normally distributed errors in the horizontal coordinates, CMAS can be
described mathematically as:

CMAS = 2.1460σc(1)

where σc is the circular standard error, which can be approximated by:

σc ≈

(

1
σx + σ y2)(2)where σx and σy are the standard deviations in horizontal
position corresponding to errors in latitude and longitude,
respectively, assuming that the larger of the two is less than
five times the magnitude of the other (Greenwalt, 1962).
SAS can be estimated as:

SAS = 2.5σ s(3)where σs is the spherical standard error approximated by:σs ≈Figure 1. HBT-TS mounted to electro-pneumatic marker with majorparts labeled.

804

(

1
σx + σ y + σz
3

)

(4)

where σz is the standard deviation in altitude, assuming that

TRANSACTIONS OF THE ASABE

1 m radius and the Dissolve Type parameter set to None,
List (using the identifier “Target_ID”), and All commands,
respectively. To determine the HUR distribution across theentire treated area, a point density analysis was performed
with a 0.0625 m2 cell size and a 1 m circular neighborhood
to measure the magnitude of the herbicide dose (0.1994 g
ae projectile-1; x = 6845) overlaid onto the total net area
footprint created by the offset placement of the projectiles.
Aspect values were extracted from a 10 m digital elevation
model layer of Maui (NOAA, 2007) at each of the offset
point coordinates to calculate the angular line of sight (L) totarget with respect to the terrain aspect (mA):the smallest of the three component standard deviations is
not less than 0.35 times the magnitude of the largest(Greenwalt, 1962).
The interquartile ranges of the spatial statistics are presented along with the standard deviations, which are composed of deliberate adjustments (e.g., offsets due to aiming
the marker at different parts of the target to disperse herbicide) in addition to some small random variation in sensor
response. Since the azimuth (θ) is capable of spanning thefull 360°, the directional mean and standard deviation arecalculated from equations 5 through 8 (Berens, 2009):s=n sin θi

L = θ − mA

(5)

i =0

c=

n

 cos θi

RESULTS AND DISCUSSION(6)An HBT application is an advancement of a surveillance
operation with the capability of immediate intervention on
high-value, incipient plant targets. One of the critical attributes of HBT is the capability to efficiently and effectively
treat targets occupying extreme terrain that are otherwise
inaccessible (fig. 2). This includes situations where the applicator can engage a target from different lines of sight (fig.
2b) or multiple targets from a single applicator position withdifferent trajectories (fig. 2c). Target engagement (upon detection) is a systematic process that momentarily deviatesfrom the normal search pattern to approach and treat the target. Consistency in these treatment actions includes a steady
position of the applicator, the attitude of the projectile, range
to target, and treatment dose (table 1). Most of these statistics
were slightly leptokurtic with a strong peak at the median,along with a minority of values as large, positive outliers,
making the averages of most distributions somewhat larger
than the corresponding medians.
The target dose had a median value of 15 projectiles
with an interquartile range from 9 to 23 projectiles. This isless than the median of an average 24-projectile dose overthe last three years of operations but is consistent with

i =0


s
 arctan 
c 

s

θ = arctan  + 180
c 


s

arctan c  + 360
 


(

s > 0, c > 0
c <0

(7)

s < 0, c > 0sθ = − 2 ln s 2 + c 2)(8)Herbicide use rate (HUR) is the amount of pesticide applied per unit area, e.g., g acid equivalent (ae) ha-1. An
HBT projectile contains 0.1994 g ae of the active ingredienttriclopyr (HBT-G4U200, Nelson Paint Co., Kingsford,
Mich.) and is estimated to produce a circular spatter patternthat has a radius of ~1 m (i.e., 3.14 m2). Spatial analyses
were performed to calculate the area of the footprint and
HUR using ArcMap 10.1 (ESRI, Redlands, Cal.). Area
footprints were calculated for each projectile, target, andtotal net treated area using the Buffer Analyses tool with

(a)

(9)

(b)

(c)

Figure 2. (a) Applicator (•) and target offset (×) locations calculated from range, azimuth, and tilt values (gray lines) overlaid on 10 m digital
elevation model, (b) a target treated from multiple applicator positions, and (c) multiple targets treated from a single applicator position.

59(3): 59(3)803-809

805

Table 1. Statistical analysis of HBT application. Range and tilt data
are from entire population of projectiles (x = 6845). All other data,
including those preceded by SD (standard deviation of theparameter), are for projectiles grouped by target (n = 365). Because
azimuth to target is semi-random for each target, only the standard
deviation of the projectile azimuth for each target is reported forthese data.
MetricMedianInterquartile Range
Average
Applicator precision and spatial statistics
CMASA (m)0.7
0.1 to 1.5
1.1
1.0
0.5 to 1.7
1.3
SASA (m)Range (m)[a]15.2
13.3 to 17.8
15.6
SD range (m)0.8
0.3 to 1.5
1.0
-33.0
-43.4 to -23.1-33.1
Tilt (°)[b]SD tilt (°)
1.0
0.7 to 1.5
1.3
3.9
2.8 to 5.5
4.9
SD azimuth (°)[c]Target offset precision
CMAST (m)1.7
1.1 to 2.3
1.9
1.9
1.3 to 2.8
2.3
SAST (m)Treatment statistics
Projectile dose[d]15
9 to 2318.7
2103.01628.5 to 2920.5
2459.7
HUR (g ae ha-1)[e][a]Distance to target measured by laser rangefinder.
[b]
Tilt measured with respect to the horizontal plane.
[c]Azimuth measured with respect to geographic north.
[d]Number of projectiles discharged during target treatment.
[e]Herbicide use rate, with 0.1994 g ae per projectile and herbicide distribution area calculated from a 1 m radius created on target impact.

smaller targets becoming more common as more matureplants are eliminated (data not shown). The marker is a
rapid fire, semi-automatic system with discharge rates of~2.2 projectiles s-1 (fig. 3). Hence, the median treatment
time is <7 s (data not shown). We suggest that the low
CMAS and SAS precision values of the applicator position
are predicated on this brief time period, while the helicopter
is holding hover (table 1). The accuracy of the target locations is unknown, as the inaccessibility of the terrain makes
ground truthing impossible. However, previous static experiments indicated that the position accuracy is comparable to that of other commercial-grade GPS units, with GPS
error being the limiting factor (Rodriguez, 2015).
The CMAS and SAS values for the target offset location
are less precise than the applicator position, where the deviations of the projectile’s range and attitude (e.g., tilt andazimuth) had a compounding effect (table 1). These varia-

tions in the recorded attitude are primarily due to operator
adjustment to cover and/or zero in on the target and accountfor 78% of the observed spread in estimated target offset
locations in CMAS and 70% of the observed spread in SAS
after accounting for random errors estimated from static
measurements. The CMAS and SAS of the target offset
locations show weak dependence on herbicide dose, andthe SAS is not substantially larger than the CMAS (fig. 4).
When a 1st/1st degree rational polynomial is fitted to the
CMAS, the resulting horizontal asymptote is 5.0 m. Thisequates to a maximum treatment diameter of 10 m, consistent with the diameter of miconia (Harling et al., 1973),
and a maximum treatment area of approximately 80 m2.
The same process for SAS shows a similar asymptote at
6.2 m, equating to a treatment volume of approximately
560 m3. If the treatment area is instead considered an annular region comprising of 90% of the deviation observed in
the azimuth and range, then the total area calculated is12.5 m2. Similarly, considering the volume bounded by
90% of the deviation seen in the azimuth, tilt, and range,
the total volume would be 9.4 m3. Adding the CMAS andSAS to these values results in an average treatment area of
16.0 m2 and treatment volume of 19.1 m3 per treated plant.
This estimate of the treatment area more closely resembles
that calculated by GIS analysis and better reflects the actual
shape of the treatment area (fig. 6b).
These aerial operations were conducted by searching formiconia occupying extreme terrain (e.g., slopes up to 70°).
Operational flight lines are typically transects running parallel to the contour, with a bias on the port side where thepilot and applicator share the same field of view, i.e., ~270° to 330° relative to the aircraft bearing, offering direct
observation by both parties of the terrain search area. Whena target was detected, the pilot approached the target to a
median distance of 15.2 m with an interquartile range notexceeding 20 m and always approached from above thetarget where the median tilt of the applicator was -33° withrespect to the horizontal plane and with an interquartile
range less than -20° (table 1). From these positions, targets
were confronted with lines of sight almost directly opposite
960

7CMAS and SAS (m)Treatment Time (s)

40
30
20
10

6
5
4
3
2
1
0

0
0

50
Projectile dose (No.)

100

Figure 3. Treatment time dependence on projectile dose ( ; n = 338;
y = 0.4572x; R2 = 0.5575). Targets requiring reload and/or applicator
repositioning (×) result in larger treatment time (outliers; n = 27).

806

8

y = 0.4572x
R² = 0.5575

50

0

50
Projectile dose (No.)

100

Figure 4. CMAS ( ) and SAS (×) of predicted target offset locations
versus projectile dose (n = 365; CMAS R2 = 0.19; SAS R2 = 0.15).
Dashed line indicates CMAS trend, and solid line indicates SAS trend.

TRANSACTIONS OF THE ASABE

0°

9000

HUR (g ae ha-1)

80

60

40

270°

6000

3000

90°

0
0

100

200

300

400

Target ID
(a)
90
80

180°

70

Figure 5. Frequency plot of projectile azimuth with respect to theterrain aspect at the predicted target location (x = 6845).
Area (m2)the terrain aspect with a median azimuth of 191° (fig. 5).
The terrain aspect is the vector normal to the terrain surface
projected into the horizontal plane and is also assumed tobe the aspect for the plant colonizer such that an angle of180° in the plot indicates application directly into the contour of the hillside (i.e., plant target). The interquartile
range was 163° to 222°, where angles >180° could indicate
efficiency in approaching the target immediately upon detection, while angles <180° might relate to efforts to reposition the aircraft for a better line of sight, free of obstacles(e.g., tree canopy). Angles measured beyond perpendicular(i.e., >270° and <90°) are improbable and most likely represent the compounding errors associated with the GPS andthe terrain model, particularly along ridges where aspect
can change dramatically with position.
Time on target (ToT) is the total time spent in the target
acquisition and treatment process. In a previous study,
Leary et al. (2014) found total search effort to be dependent
on target density, where the slope value was equivalent tothe added time for every target encountered (i.e., ToT). The
actual treatment time recorded as the time interval between
the first and last projectile discharged was a minor timeelement in these operations (table 2). The majority of thetime appears to have been spent approaching and maneuvering the applicator into position for target treatment.
Time spent reloading projectiles (19.1 ±8.3 s) and repositioning the applicator (20.1 ±10.8 s) were other time elements contributing to ToT, although these activities were

60
50
40
30
20
10
0
0

10
Projectile dose (g ae)

20(b)
Figure 6. (a) Target herbicide use rate (HUR; g ae ha-1; n = 365; x =6845) calculated from the projectile dose and net area of the projectile
offset locations buffered with a 1 m radius, and (b) net target offset
area created by projectile dose. Green dashed line is the HUR for asingle isolated projectile, and red dashed line is the maximum allowable HUR according to the registered pesticide label.

not required for the majority of targets treated.
A single projectile creates a treatment footprint area estimated at 3.14 m2 with an equivalent HUR of 634.7 g ae
ha-1, which is 9.4% of the maximum allowable rate (i.e.,
6,720 g ae ha-1 year-1). The mean target HUR in these operations was 2,460 g ae ha-1, with 98.3% of targets below the
maximum HUR (fig. 6a). The average target dose and area
footprint were 3.6 g ae and 15.1 m2 for targets below the
maximum HUR (fig. 6b). On the other hand, for those six
targets that exceeded the maximum HUR, the average area
footprint was only slightly higher at 17.2 m2, while the average dose increased to 13.8 g ae. These high doses are

Table 2. Time elements of the target acquisition and treatment process.
Activity
Characteristic
Time (s)Time spent at a target not in active search
Total time
55.5 ±4.9Time to administer projectile dose to target
Time between first and last projectile discharged
9.2 ±6.5
Reloading hopper with projectiles,
Reload every ~160 projectiles
19.1 ±8.3interrupting treatment action
Reposition time
Relocating to treat target from a different location
Standard deviation of azimuth and range of target
20.1 ±10.8
increase substantially[a]Time on target was extrapolated from the slope of search effort dependent on target densities encountered, as described by Leary et al. (2014).
Treatment time (n = 338), reload time (n = 20), and reposition time (n = 7) were direct empirical values derived from the time stamps.
Name[a]Time on target
Treatment time
Reload time59(3): 59(3)803-809

807

REFERENCES

HUR (g ae ha-1)

15000

10000

5000

0
0.00

0.25

0.50

0.75

1.00

pixel:net area
Figure 7. Cumulative distribution plot of pixel-scale (0.0625 m2) HUR
for the entire area treated in this study. Red dashed line is the maximum allowable HUR.

likely artifacts of treating larger (mature) targets or due toinaccuracies in treating smaller targets. The total area footprint of these excessive targets was 103 m2, or 1.9% of thetotal target area. The total net area footprint was 4,938 m2,
which was saturated 435.5% by the gross projectile footprint area (i.e., 3.1416 m2 × 6845 projectiles), with a net
HUR that was 41.1% of the maximum allowable rate. In
this case, 6.1% of the total pixel area (i.e., 371.1 m2) exceeded the maximum HUR (fig. 7) but was heterogeneously scattered at a sub-meter scale. The analyses of HBT-TS
data highlight the fine-scale presentation of herbicide application and the opportunity for high-resolution analyses.

CONCLUSION
The HBT platform is a precision pesticide application
system customized for incipient species control where operational performance has both spatial and temporal relevance. The second-phase HBT-TS with LRF has substantially enhanced the resolution of this data-driven processwith the capability to (1) accurately measure treatment
time, (2) better interpret applicator position and approach totarget, (3) geometrically calculate target offset location, and(4) determine HUR with high resolution. While precision isa highlight of the HBT-TS, accuracy remains a challenge
for all technologies that rely on GPS in a dynamic environment. Future work is proposed to investigate the transition of this technology proven in manned aerial systems
toward adoption in unmanned aerial systems.
ACKNOWLEDGEMENTS
This project was funded in parts by the USDA Forest
Service Special Technology Development Program (Award
R5-2012-01) through collaboration with the Hawaii Department of Land and Natural Resources Forest Health Program,the Hawaii Invasive Species Council, the USDA Hatch Act
Formula Grant Project 112H, and the Maui County Office of
Economic Development and Department of Water Supply.

808

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Stone, C., & Scott, J. M. (1985). Hawaii’s Terrestrial Ecosystems:
Preservation and Management. Honolulu, Hawaii: University of
Hawaii: Cooperative National Park Resources Studies Unit.
Stone, C., & Smith, C., & Tunison, J. T. (Eds.). (1992). Alien Plant
Invasions in Native Ecosystems of Hawaii: Management andResearch. Honolulu, Hawaii: University of Hawaii Press.

TRANSACTIONS OF THE ASABE

USBB. (1947). United States National Map Accuracy Standards.
Washington, D.C.: U.S. Bureau of the Budget.

NOMENCLATURE
CMAS = circular mapping accuracy standard
EMW = East Maui Watershed59(3): 59(3)803-809

HBT = Herbicide Ballistic Technology
HBT-TS = HBT telemetry system
HUR = herbicide use rate
LRF = laser rangefinder
SAS = spherical accuracy standard
SD = standard deviation (for a single target)
ToT = time on target

809

2078

IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015

Design and Validation of a GPS Logger System
for Recording Aerially Deployed Herbicide
Ballistic Technology Operations
Roberto Rodriguez, III, Student Member, IEEE, Daniel M. Jenkins, and James J. K. Leary
Abstract— Herbicide ballistic technology (HBT) is an electropneumatic delivery system designed for administering 17.3-mm
herbicide-filled projectiles (e.g., paintballs) to visually acquired
weed targets. Currently, HBT is being deployed from a Hughes
500D helicopter platform in aerial surveillance operations toeliminate satellite invasive weed populations in remote natural
watershed areas of Maui (HI, USA). In an effort to improve
operations, we have integrated GPS and other sensor hardware
into the electropneumatic device for instantaneous recording oftime, origin, and trajectory of each projectile discharged by theapplicator. These data are transmitted wirelessly to a custom
android application that displays target information in real time
both textually and graphically on a map.
Index Terms— Data acquisition, geospatial analysis, global
positioning system, sensor integration and fusion.

I. I NTRODUCTION
NVASIVE, exotic plant species are threatening the endemic
biological integrity of the Hawaiian archipelago [1]–[7].
Moreover, the islands’ extreme topography and dense vegetation are an impediment to effective mitigation [8]. Herbicide
Ballistic Technology (HBT) is a concept to address thesechallenges with a novel capability to treat invasive plant targets
with long-range accuracy [9]. In previous implementations,the HBT platform enhances helicopter surveillance operations
with the capability of eliminating high-risk satellite populations of invasive plant targets, which are occupying remoteinaccessible areas of watershed [10].

I

II. BACKGROUND
The HBT platform is an herbicide delivery system currently
registered in the state of Hawaii as a Special Local Need pesManuscript received September 15, 2014; revised November 3, 2014;
accepted November 11, 2014. Date of publication November 20, 2014; dateof current version January 29, 2015. This work was supported in part by
the U.S. Department of Agriculture (USDA) Forest Service, in part by theSpecial Technology Development Program under Award R5-2012-01 throughthe Hawaii Department of Land and Natural Resources Forest Health Program,in part by the Hawaii Invasive Species Council under Award POC 40466, inpart by the USDA Hatch Act Formula Grant under Project 112H, and inpart by the USDA Renewable Resources Extension Act. The associate editor
coordinating the review of this paper and approving it for publication was
Prof. Octavian Postolache.
R. Rodriguez III and D. M. Jenkins are with the Department of Molecular
Bioscience and Biological Engineering, University of Hawaii at Manoa,
Honolulu, HI 96822 USA (e-mail: roberto6@hawaii.edu; danielje@
hawaii.edu).
J. J. K. Leary is with the Department of Natural Resources andEnvironmental Management, University of Hawaii at Manoa, Honolulu,
HI 96822 USA (e-mail: leary@hawaii.edu).
Color versions of one or more of the figures in this letter are available
online at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/JSEN.2014.2371896

ticide for treating nascent miconia (Miconia calvescens DC)
and strawberry guava (Psidium cattleianum) patches in remotenatural areas [9]. The basic concept of HBT is the encapsulation of an active herbicide formulation into 17.3 mm soft-gel
projectiles (i.e., paintballs) for accurate, long-range delivery to
weed target via propulsion from an electro-pneumatic marker.
Projectiles can be delivered to a target with an estimatedeffective range of ∼30m, presenting novel opportunities for
managing areas with extreme, inaccessible landscapes (e.g.,ravines and cliff faces).
The adoption of satellite navigation (utilizing GPS andGLONASS) in HBT operations has allowed for the acquisitionof large data sets leading to explicit spatial and temporal
performance evaluation of an operation [10]. Current
op erational procedures call for reference points to be recorded
for each target treated using a consumer-grade GPS receiver
capturing latitude, longitude, elevation and timestamp. At theend of each operation, the applicator also records the estimatedtotal consumption of projectiles that is later translated into
the average dose rate for the total targets treated in that
operation.
Attitude and heading reference systems (AHRS) provide
the roll, pitch and yaw of a body and are commonly used
for navigation purposes. Recent development in micro-electromechanical systems (MEMS) based AHRS systems are being
used in a number of applications, including unmanned aerial
vehicles (UAV) [11], commercial airplanes [12], along withterrestrial [13] and submerged navigation [14]. However, manyof these systems have a large profile and require wired
connections to data recording devices making them ill suitedfor implementation with the HBT platform.
To enhance operational data acquisition, a custom, prototype
HBT-Logging System (HBT-LS) was developed for integration
with the electro-pneumatic marker automating data acquisition
for every projectile discharged. Data acquired includes theabove mentioned spatial and temporal assignments, alongwith added attributes for tilt and azimuth of the marker
position (Fig. 1). New analyses of HBT-LS data sets include:(i) accurate accounts of projectile dose rates assigned to eachtarget, (ii) the time to deliver projectile dose to target and(iii) offset projections of the actual target location.
Here in, we report on the basic hardware and software specifications of HBT-LS with static and dynamic calibrations incontrolled and operational settings, respectively. This includes
a discussion on improvements in the data management process
and technology limitations requiring further development.

1530-437X © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

RODRIGUEZ et al.: DESIGN AND VALIDATION OF A GPS LOGGER SYSTEM

2079

Fig. 1. Spherical coordinate system to describe plant target locations withapplicator as the origin.

III. S ENSOR D EVELOPMENT
A. Hardware Design
The relevant data to be recorded include the position (latitude, longitude, and altitude), azimuth and tilt of the marker,
depicted in Fig. 1, as well as each discharge of a projectile
and the unique target IDs and descriptions of each targeted
plant. Latitude and longitude are recorded within a custom
Android user interface from the built in GPS chip (Broadcom
BCM4751) on the interfacing Android device. Most non-GPS
information is recorded on a custom circuit (Fig. 2) withindividual sensors communicating to a simple 8-bit microcontroller (ATMEGA328P-MUR, Atmel Corp., San Jose, CA)
which transmits data wirelessly to the Android application
through a serial Bluetooth module (RN42, Roving Networks,
Los Gatos, CA). Altitude is estimated from barometricpressure measurements based on empirical relationships(MPL3115A2, Freescale Semiconductor, Austin TX). Azimuth
and tilt are recorded from inertial (MPU-6050, InvenSense,
San Jose, CA) and magnetic (LSM303DLHTR, STMicroelectronics, Geneva, Switzerland) sensors as described below.
Projectile discharge is identified by an interrupt triggered by
the transistor sinking the solenoid current in the marker, andsimilarly a momentary contact switch triggers an interrupt
to indicate acquisition of a new target (for which a newtarget ID is automatically assigned). Descriptive informationfor each target is coded by user selection of radio buttons in the
Android interface. In our case, descriptions are coded for thedevelopmental stage of the plant with options for “Juvenile”(not yet bearing fruits/seeds), “Mature” (flower/fruit bearing),
or “Survivor” (showing sub-lethal symptoms resulting froma previous herbicide application). Description reverts to thedefault “Juvenile” for each newly engaged target, as these areby far the most commonly encountered plants in our operations
to eliminate incipient satellite populations.

Fig. 2. HBT-Logger System (HBT-LS) with annotations for major components (top), and mounted on rail attachment system (bottom).

1) Altitude: Altitude is automatically inferred fromobserved barometric pressure (MPL3115A2, Freescale Semiconductor) based on the following internal empirical relationship, by setting the “ALT” bit on Control Register 1 of thesensor: 0.1902632
p
h = 44330.77 1 −(1)+ h off
p0
where h is the height (in meters), p is the pressure (in Pascals),
p0 is the sea level pressure, and h off is the offset in thedetermined height. To calibrate for variations in barometricpressure, sensors are calibrated at the start of each operation
based on the known elevation at the landing site. This known
elevation is used by the calibration activity of the Android
device to estimate the current sea level pressure based on
the current barometric pressure and its empirical relationshipwith altitude. The new estimate of sea level pressure reference
is communicated to the microcontroller and loaded into the“Barometric Pressure Input” Registers of the MPL3115A2.

2080

2) Azimuth and Tilt: The azimuth and tilt, represented by θand ϕ in a spherical coordinate system (Fig. 1), are recorded
using a triple axis gyroscope/accelerometer (MPU-6050)
and a triple-axis tilt-compensated magnetic compass(LSM303DLHTR). Redundant measurements of orientation
were made from these devices to facilitate identification andcompensation for drift in the azimuth estimated from thegyroscope, or deviations in compass readings resulting fromlocal disturbances in geomagnetic field or interferences bymagnetic fields originating from or shielded by the aircraft.
The calibration activity of the Android interface allows
the user to overwrite the digitized values stored in device
EEPROM corresponding to the maximum and minimum
magnetic fields applied in each axis of the compass chip(which vary significantly between devices). This allows themeasurements in each axis to be scaled to internally consistentmeasures of the field strength. This calibration requires theuser to align each of 6 reference orientations (+x, −x,+y, −y, +z, −z) of the sensor coordinates with the peakgeomagnetic field at the given location. As a result, the3-D vector of any arbitrary magnetic field is estimated accurately with respect to the marker coordinate system, and vector
operations are implemented by the microcontroller to project
this vector onto a horizontal plane compensated for tilt androll of the marker estimated from acceleration measurementson the same chip. These measurements provide an estimateof the orientation of the marker in the horizontal plane withrespect to magnetic north. Marker orientation is estimated fromthe gyroscope readings using custom coded quaternion algebraon the quaternion output retrieved from the digital motion
processor of the device using the manufacturer’s software
library (MotionAppsTM 5.0). The quaternion codes for thecurrent orientation of the sensor with respect to the initialorientation at the startup of the sensor.
Magnetic declination is determined at the start of each
operation by orienting the marker along a path aligned withtrue north (or any other given reference orientation) and communicating this reference orientation to the microcontroller
so that the reference with respect to magnetic north can berecorded in EEPROM. On device startup (or recalibration), themarker orientation estimated by the gyroscope, projected onto
the horizontal plane, is initialized to the current geographicalorientation based on the tilt compensated compass reading
corrected for magnetic declination. The marker position(latitude, longitude and altitude), azimuth, and tilt, as depicted
in Fig. 1, can be used to infer target position based on
overlaying projectile orientation and trajectories onto digital
elevation maps, and/or using an estimated range to target,
represented by ρ.
3) Trigger Detection: The electro-pneumatic marker
discharges projectiles via an actuating solenoid. Projectile
discharge is registered by an interrupt caused by a falling edgeof this signal, using a custom implemented Schmitt Trigger
to prevent multiple interrupts from a single transition andto shift the signal to the microcontroller logic level. The
trigger signal is buffered by a voltage follower to prevent
loading of the solenoid. In order to prevent triggering from
artifacts of resonance in the inductive load associated withIEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015

the same trigger pull, a latent period is enforced in software
during which subsequent falling edges are not registered. Thislatent period is greater than the period for which oscillations
associated with a single projectile discharge occur, but issmaller than the period at which projectiles can be discharged
in rapid fire (i.e., >10 projectiles sec−1 ).
B. Software Design
1) Calculating Plant Target Coordinates: The equations of
motion for a spherical projectile travelling in air is [15]



1

  v − W
m r¨ = mv˙ = − ρ A AC D v − W
2




 ω

 × v − W1+ ρ A AC L v − W
+ mg
2
ω
(2)
where m is the mass of the projectile, r is the position of
the projectile in Cartesian coordinates relative to the origin,v is the velocity of the projectile relative to the Cartesian
coordinate system, ρ A is the air density, A is the crosssectional area of the projectile, C D is the (dimensionless) dragcoefficient, W is the velocity of the wind blowing relative tothe same coordinate system, C L is the (dimensionless) lift
coefficient, ω is the angular velocity of the projectile andmg is the gravitational force. Due to the highly dynamic natureof wind conditions in close proximity to the helicopter, theshort range of HBT application, and the relatively large initial
velocity of the projectiles, a simplification to linear trajectories
is made for real time calculations. However, since all raw datais also recorded more rigorous analysis based on the data isalso possible.
The azimuth, tilt, and range describe the location of thetarget relative to the applicator in a local spherical coordinate
system centered at the applicator. In order to superimpose thelocal coordinates of the target over the geodetic coordinatesof the applicator, the local spherical coordinates are converted
into local Cartesian coordinates with a North-East-Down
reference frame centered at the applicator using the following
relationships:
x A→T = ρ cos ϕ cos θ
y A→T = ρ cos ϕ sin θ

(3)
(4)

z A→T = ρ sin ϕ(5)where x, y, and z (with subscript A→T) designate thecomponents of the vector from applicator to target in local
Cartesian coordinates and ρ, θ and ϕ describe the vector
in local spherical coordinates. The short range of an
HBT application relative to the radius of the Earth allows for
simplified calculations using a local flat surface projection.
The final target offset coordinates are calculated from thefollowing relationships:
x A→T
(6)
φT = φ A +R Eart hy A→T(7)
λT = λ A +R Eart h cos φ A
h T = h A + z A→T(8)

RODRIGUEZ et al.: DESIGN AND VALIDATION OF A GPS LOGGER SYSTEM

2081

Fig. 3. Errors due to assumptions of flat surface projection (black arrows)
include discrepancies of the azimuth and longitude that are dependent on thelatitude. Blue dashed lines represent the actual “lines” of constant longitude
that converge as latitude increases.

where φ, λ and h are geodetic coordinates (with subscripts T
for target or A for applicator) and R Eart h is the radius of the
Earth [16].
The flat surface approximations result in latitude-dependent
errors in the estimated values of the azimuth to and longitudeof the target (Fig. 3). Using the prefix “” to designate theerror in a parameter, errors in the target geodetic coordinates
can be estimated from basic uncertainty analysis assuming thaterrors in each measurement are random and independent:
φT ≈
λT ≈

(φ A )2 + (ξφ (φ A ))22(λ A )2 + ξλ (φ A )h T =(h A )2 + (ρ cos ϕ)2 + (ρ sin ϕϕ)2 (11)

(9)
(10)

where ξ (φ A ) is the error due to the flat surface approximation
as a function of the applicator’s latitude. Due to the shortrange of the HBT application relative to the radius of the
Earth, ξ (φ A ) is relatively small compared to the horizontal
and vertical errors in the GPS receiver. For example,
at the approximate latitude of 20.8°, where these tests wereconducted, with a range of 30 m and azimuth at 45°, the valueof ξ (φ A ) is less than 10−6 ° based on comparison with themore rigorous Vincenty formulae using the WGS-84 model,
equivalent to about 0.1 m [17].
2) Microcontroller: Machine code was generated using
the Arduino IDE (Arduino, Torino, Italy), and programmed
onto the microcontrollers (ATMEGA328P-MUR) using software (Atmel Studio 6.1) and programming hardware(AVRISP-mkII) from the manufacturer (Atmel). During
normal operation, the microcontroller polls all of the sensors
for new data each cycle of the program. Any new data is sent toa paired Google Nexus 7 tablet (Asus Computer International,
Fremont, CA) over Bluetooth. Each set of data is preceded bya code uniquely identifying the type of data being sent (i.e.
orientation, tilt, altitude, projectile discharge, or acquisition of
new target) so that the Android Bluetooth Service can parsethe incoming data and update the user interface appropriately.

Fig. 4. User interface showing flight path and trajectories of projectiles
for a single HBT operation (note that the HBT-LS is not connected so thatmarker orientation is not displayed, and target and projectile counts are reset
to zero). Options available through the options button include connecting or
disconnecting to logger over Bluetooth, starting or ending a record of data,e-mailing or displaying recorded data on the map, and launching otheractivities such as system calibration.

In addition, each batch of data is followed by a custom
check code to validate correct transmission of data. Any datathat does not contain a valid code and a correct check code
is discarded by the Android device without further action.
Because data is continuously streamed to the Android device
and only the most recent data is recorded to associate withperiodic trigger pulls and trackpoints, no attempt to recoverincomplete data strings is made.
3) User Interface: An Android device is used to record
data, allow the user to send commands (i.e. for calibration)
to the microcontroller, and to display device data in realtime both textually and on a map (Fig. 4). The custom
Android application was developed using the Eclipse IDE
to record GPS coordinates, parse incoming Bluetooth datatransmitted from the custom hardware, record all data to acomma-delimited file, and update the user interface (withtextual and map information) in real-time. An options menu
on the main activity interface allows the user to connect

2082IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015

Fig. 5. Predicted locations and associated CMAS for Foretrex 401 (red), Google Nexus 7 (green) and HBT-LS (blue). Reference antenna location is marked
with a black X at the origin.

wirelessly to different custom hardware, start and end data
logging, display recorded data on the map, or launchother activities such as the calibration options described
previously.
IV. S TATIC ACCURACY AND P RECISION OF HBT-LS
According to the National Standard for Spatial Data
Accuracy (NSSDA), the accuracy of a GPS receiver is determined by root mean square error (RMSE), which is the squareroot of the average of the sum of the squared differences
between the coordinate values from a GPS receiver relative
to another more accurate source of the same position used asa reference position [18], [19].
Precision of a GPS receiver in the horizontal x andy directions (aligning respectively with lines of constant longitude and latitude), is described by the circular map accuracy
standard (CMAS), which is based on the US National Map
Accuracy Standards specifying that “no more than 10% of
the points in the dataset will exceed a given error” [20].
Therefore, the CMAS is defined as the magnitude of the radiusof the smallest circle containing 90% of the recorded positions.

Fig. 6. Accuracy and precision statistics for Foretrex 401, Google Nexus 7
and HBT-LS.

Assuming normally distributed errors in the horizontal coordinates CMAS can be described mathematically as
C M AS = 2.1460σc(12)RODRIGUEZ et al.: DESIGN AND VALIDATION OF A GPS LOGGER SYSTEM

2083

TABLE IH ERBICIDE D OSES (G RAMS OF A CID E QUIVALENT TARGET−1 ) D ERIVED F ROM
HBT-LS C OMPARED TO C OMPOSITE AVERAGES

Fig. 7. Deviation in gyroscope bearing with respect to compass bearings (in degrees) over time, for stationary logger unit with sensor z axis (×) or y axis(+) aligned with vertical/gravitational force, or recorded under dynamic conditions over the course of three separate airborne operations (circles, squares, andtriangles). Symbols without fill are trackpoint data during aerial operations, and red filled symbols are associated with projectile discharges. To remove clutter
data was decimated leaving only every 10th data point.

where the circular standard error σc can be approximated by
1
σx +σ y(13)
σc ∼2
where σx and σy are the standard deviations in horizontal
position corresponding to errors in latitude and longitude,
respectively, assuming that the larger of two is less than 5x
the magnitude of the other [21].

Precision of a GPS receiver in three dimensions, including
the z (vertical) direction, is given by the Spherical Accuracy Standard (SAS), which is defined as the magnitudeof the radius of the smallest sphere containing 90% of therecorded positions. This value can be estimated as
S AS = 2.5σs

(14)

2084

where σs is the spherical standard error approximated by
1
σx +σ y +σz
(15)
σs ∼
3
where σz is the standard deviation in altitude, assuming thatthe smallest of the three component standard deviations is notless than 0.35x the magnitude of the largest [21].
On July 20, 2014, calibrations were performed with the
HBT-LS and other consumer-grade GPS receivers against a
GPS reference station (Trimble NetRS: 21° 17 50.46 N,
157° 48 58.95 W, 81.378m above sea level) located in
Honolulu, HI. The consumer-grade GPS units calibrated inthis study included a Google Nexus 7 tablet independent of the
HBT-LS and the Foretrex 401 handheld (Garmin Olathe, KS).
These GPS units were placed at the base of the reference
station antenna on the roof and their positions recorded
every 5 seconds for 3 hours. With the sensor board mounted
to the marker, the HBT-LS was mounted in an articulated
vise (PanaVise 350, Reno, NV) at a horizontal distance ofapproximately 18 meters from and aligned azimuth to target the reference position with azimuth 290°. In this attitude data was recorded by the HBT-LS every 5 seconds
for 3 hours. Accuracy for all test receivers was determined
by RMSE relative to the known reference position, while
precision was determined by radial magnitudes for CMAS
and SAS as described above. The reference position was
estimated from HBT-LS data using the known distance totarget to completely define the vector from marker to thereference.

IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015

Fig. 8. Deviation in tilt estimate from gyro with respect to tilt estimate
from compass, for data in a single aerial operation. Red filled symbols aredata associated with a projectile discharge, and unfilled symbols are fromtrackpoint data. Data are decimated to show only every 10th data point toremove clutter.

consumed (∼160 projectiles per pod) by the total number oftargets treated in an operation, with rounding errors
expected [9].
VI. R ESULTS

V. DYNAMIC ACCURACY AND P RECISION IN O PERATIONS
Aerial surveillance operations were conducted in 2014
targeting Miconia calvescens and Psidium cattleianum weed
populations on Maui with the HBT-LS integrated to theelectro-pneumatic marker. Operations were conducted using
a Hughes 500D helicopter with the applicator positioned on
the port side behind the pilot as described by Leary et al. [10].
In these operations, the HBT-LS recorded all projectiles
discharged with timestamp and target assignment along withall other calibrated sensor information. Operational data were
evaluated to determine the distribution of projectile trajectories
with respect to the nose of the aircraft and the horizontal plane.
For a data subset (n = 362) an additional HBT-LS was
positioned at the nose for calculation of the angle between
the applicator and aircraft azimuths and bearing for comparison with the horizontal target window (i.e., 270° to 330°)
corresponding to the shared view of the pilot and applicator.
Tilt values were compared to the vertical target window(i.e., 0° to −50°). Altitude above ground level (Altagl ) was
estimated as the difference between the elevation inferredfrom the barometric pressure readings and the raster pixel
value of the digital elevation model (DEM; 10m resolution)corresponding to the recorded point location.
Herbicide dose accuracy was measured as the percent
difference between mean target dose rate recorded by HBT-LS(average number of projectiles used to treat each uniquetarget ID) and composite averages in each operation estimatedby dividing the total number of pods (projectile containers)

A. Accuracy and Precision of Target Coordinates
Both HBT-LS and tablet exhibited static circular and spherical precisions about seven times smaller than the corresponding values recorded for the handheld GPS unit (Fig. 5).
Accuracy (RMSE) of the tablet was also superior to the otherGPS unit in 2D and 3D, while the HBT-LS was superior tothe handheld GPS in 3D accuracy (Fig. 6). Moreover, it isworth noting how the BCM4751 receivers of the HBT-LS
and tablet were coinciding with much more stable plots ofthe coordinates in the short three hour period compared to
the widely dispersed random appearance of the handheld GPS(see Fig. 6). The HBT-LS points are shifted further from thereference point, which is likely due to compounding errors
exhibited by the tilt and azimuth sensors used for determining
the target location and approximations made in installation andoffset calculation.
B. Operational Validation
The HBT-LS successfully acquired data from seven independent operations in 2014 for a total of 11,132 projectiles assigned to 400 targets. Android tablets never became
disconnected, textual data displayed on the app was constantly refreshed during operations, and the system was neverobserved to miss a trigger pull during operation, suggestingthat the data communication was robust. By assigning target
IDs to each projectile with the HBT-LS, we were able toqualitatively identify the target dose outliers (i.e., a large target

RODRIGUEZ et al.: DESIGN AND VALIDATION OF A GPS LOGGER SYSTEM

2085

Fig. 9. Altitude above ground at the point of application estimated from elevation measurements from the HBT-LS (n = 11, 724) and Foretrex 401 (n = 11, 745)with ground level inferred from a 10-m digital elevation model at the recorded location.

treated with large projectile quantity) and also calculate meanvalues with standard deviations for each operation (Table I).
In total, the HBT-LS mean (± standard deviation) calculations were within 11% of the composite estimated values.
Anecdotally, herbicide dose corresponds to weed target size,
so that HBT application data can be useful for assessing
population age and phenology across the geographical range
of operations. The standard deviations observed in this data set
were rather large relative to the mean, suggesting diverse target
populations. The capability of generating standard deviations
will enhance interpretations with measures of uniformity andfor segregating target outliers based on size class.
Efforts to determine the accuracy of the azimuth offset
relative to the target window deduced from the track vector
bearing were prone to large errors, particularly when theaircraft was in a stationary hover and pivoting on its axis
(data not shown) such that the track direction did not coincidewith the aircraft orientation. Despite a large interquartile range,
the most frequent azimuth offset estimated for applicatorrelative to aircraft nose under these conditions was 311°.
Vertical tilt estimates, on the other hand, were independentof aircraft bearing and so had a much tighter interquartile
range of −20° to −41°. The more limited azimuth data subset
relative to aircraft orientation recorded simultaneously by aseparate logger in the cockpit displayed an interquartile range
from 292° to 335°, contained within the perceived target
window.
The average time on target (time interval between the firstand last projectile discharged) was 12.3 ± 9.8 s.
To determine the stability of the gyroscope readings ofazimuth and tilt (relative to those from the digital compass
readings) were recorded both under static and dynamic conditions, and plotted against time (Figs. 7 and 8 respectively).

Stationary data indicated that gyroscope readings have small
axis-dependent biases in rotational velocity, which does
not completely explain the relatively large systematic drift
observed during aerial operations. Furthermore, the systematic drift experienced during aerial operations is not
explained by random integration errors in the digital motion
processor on the MPU-6050. This suggests that vibration or other motion artifacts might superimpose significant
biases onto the rotational velocity measurements around thevertical axis, for example by inducing sympathetic vibrationsin the gyroscope oscillators at odd harmonics. The deviation in tilt is not subject to this systematic drift, as thedigital motion processor in the gyroscope chip corrects fordrift in the tilt measurements based on acceleration (gravity)
measurements in the different axes. No systematic drift wasobserved in stationary measurements of the digital compass.
In addition, compass bearing to targets in operational data
corresponded closely to expectations in that application is
primarily against weed targets populating cliffsides, so that
trajectories were more or less perpendicular to contoursof terrain maps in the direction of increasing elevation.
These data suggest that the aircraft did not significantly distortor shield local geomagnetic fields, and that at least in the areasof our operations there are little if any local distortions in thefield.
The Altagl values (applicator elevation estimated from barometric pressure relative to ground surface elevation estimatedfor the corresponding GPS position on 10m digital elevation
model) estimated from operational data recorded from the
HBT-LS and consumer-grade GPS, were highly variable andincluded some negative values (Fig. 9). It should also be notedthat some dramatic weather changes occurred during several of
the operations which likely confounded many of the altimeter

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IEEE SENSORS JOURNAL, VOL. 15, NO. 4, APRIL 2015

estimates based on the calibrated barometric pressure at thestart of operations and correspondingly contributed to errors
in Altagl .
VII. C ONCLUSION
The HBT-LS provided satisfactory accuracy and precision
relative to consumer-grade handheld GPS units currently inuse, enhanced data acquisition with new spatial and quantifiable attributes, while maintaining a low profile relative to themarker. Testing in an operational setting showed that results
are consistent with anecdotal observation and expectations.
Improvements in altimeter recordings may be necessary forbetter determination of offset locations to targets. Implementation of laser rangefinders to determine the range to theplant target and altitude will further improve the utility of
the logger and enable direct estimation of target location
without requiring knowledge of elevation and reference todigital elevation maps. Use of a single chip 9 axis sensor andadditional sensor fusion between the accelerometer, gyroscopeand magnetic compass for improved bearing determination
should also be implemented. While this system was developedfor use with the HBT platform, alternative applications include
the use of marking agents to track the positions of plants
and animals, including invasive species or livestock, surveying
difficult to reach terrain, and spatial analysis of video and still
imagery recorded by UAVs.

[10] J. J. K. Leary et al., “Reducing nascent miconia (Miconia calvescens)patches with an accelerated intervention strategy utilizing herbicideballistic technology,” Invasive Plant Sci. Manage., vol. 7, no. 1,
pp. 164–175, Jan. 2014.
[11] J. S. Jang and D. Liccardo, “Automation of small UAVs using a low cost
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Auto. Underwater Veh. (AUV), Sep. 2012, pp. 1–8.
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ACKNOWLEDGMENT
The authors would like to thank Dr. J. Foster and the Pacific
GPS Facility for allowing use of their GPS reference station
for accuracy and precision experiment.
R EFERENCES[1] G. W. Cox, Alien Species in North America and Hawaii, 1st ed.
Washington, DC, USA: Island Press, 1999.
[2] L. Loope and F. Kraus, “Preventing establishment and spread of invasive species: Current status and needs,” in Conservation of Hawaiian
Forest Birds: Implications for Island Birds, New Haven, CT, USA:
Yale Univ. Press, 2009.
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from displacement by invasive plants on Maui, Hawaii,” Weed Technol.,vol. 18, pp. 1472–1474, Dec. 2004.
[4] H. A. Mooney and J. A. Drake, “Ecology of biological invasionsof North America and Hawaii,” in Ecological Studies: Analysis andSynthesis. Berlin, Germany: Springer-Verlag, 1986.
[5] C. P. Stone and J. M. Scott, Hawaii’s Terrestrial Ecosystems: Preservation and Management, 1st ed. Honolulu, HI, USA: Univ. Hawaii Press,
1985.
[6] C. P. Stone, C. W. Smith, and J. T. Tunison, Alien Plant Invasions in
Native Ecosystems of Hawaii: Management and Research. Honolulu,
HI, USA: Univ. Hawaii Press, 1992.
[7] D. B. Lindenmayer, C. R. Margules, and D. B. Botkin, “Indicators of
biodiversity for ecologically sustainable forest management,” Conserv.
Biol., vol. 14, no. 4, pp. 941–950, 2000.
[8] C. Kueffer and L. Loope, “Prevention, early detection and containmentof invasive, nonnative plants in the Hawaiian Islands: Current efforts
and needs,” Dept. Botany, Univ. Hawaii at Manoa, Honolulu, HI, USA,
Tech. Rep. 166, Aug. 2009.
[9] J. J. K. Leary, J. Gooding, J. Chapman, A. Radford, B. Mahnken,
and L. J. Cox, “Calibration of an herbicide ballistic technology (HBT)
helicopter platform targeting Miconia calvescens in Hawaii,” Invasive
Plant Sci. Manage., vol. 6, no. 2, pp. 292–303, Jan. 2013.

Roberto Rodriguez, III (M’14) received the B.S. degree in biologicalengineering from the University of Hawaii at Manoa, Honolulu, HI, USA,
where he is currently pursuing the M.S. degree in biological engineering.
He has been a Research Assistant with the Department of Molecular
Biosciences and Biological Engineering, University of Hawaii at Manoa, since2013, and a member of the American Society of Agricultural and BiologicalEngineers since 2014. His current research interests include the use of remotesensing for environmental and medical applications.

Daniel M. Jenkins received the B.S. and M.Eng. degrees in agricultural andbiological engineering from Cornell University, Ithaca, NY, USA, in 1995
and 1996, respectively, and the Ph.D. degree in biological and agricultural
engineering from the University of California at Davis, Davis, CA, USA, in
2001.
He has been a faculty member with the Department of Molecular
Biosciences and Bioengineering, University of Hawaii at Manoa, Honolulu,
HI, USA, since 2002, a member of the American Society of Agricultural andBiological Engineers since 1998, and a member of the American Chemical
Society since 2005. His primary interest is in molecular and other sensor
systems for agricultural and environmental applications.

James J. K. Leary received the B.S. degree in horticulture with a minor
in chemistry from Michigan State University, East Lansing, MI, USA, in
1996, and the M.S. degree in horticulture and the Ph.D. degree in molecular
biosciences and biological engineering with a specialization in weed scienceand molecular ecology from the University of Hawaii at Manoa, Honolulu,
HI, USA, in 1999 and 2006, respectively.
He has served as a faculty member with the Department of Natural
Resources and Environmental Management, University of Hawaii at Manoa,
since 2009, where he ranked as an Assistant Specialist with a research andextension split appointment. His interests are applied research in invasive plant
species management.

Invasive Plant Science and Management 2014 7:164–175

Reducing Nascent Miconia (Miconia
calvescens) Patches with an Accelerated
Intervention Strategy Utilizing Herbicide
Ballistic Technology
James Leary, Brooke V. Mahnken, Linda J. Cox, Adam Radford, John Yanagida, Teya Penniman, David C. Duffy, andJeremy Gooding*
The miconia (Miconia calvescens) invasion of the East Maui Watershed (EMW) started from a single introduction over
40 yr ago, establishing a nascent patch network spread across 20,000 ha. In 2012, an accelerated intervention strategy was
implemented utilizing the Herbicide Ballistic Technology (HBT) platform in a Hughes 500D helicopter to reduce target
densities of seven nascent patches in the EMW. In a 14-mo period, a total of 48 interventions eliminated 4,029 miconia
targets, with an estimated 33% increase in operations and 168% increase in recorded targets relative to the adjusted meansfrom 2005 to 2011 data (prior to HBT adoption). This sequence of interventions covered a total net area of 1,138 ha,creating a field mosaic of overlapping search coverage (saturation) for each patch (four to eight interventions per patch).
Target density reduction for each patch fit exponential decay functions (R 2 . 0.88, P , 0.05), with a majority of thetarget interventions spatially assigned to the highest saturation fields. The progressive decay in target density led toconcomitant reductions in search efficiency (min ha21) and herbicide use rate (grams ae ha21) in subsequentinterventions. Mean detection efficacy (6 SE) between overlapping interventions (n 5 41) was 0.62 6 0.03, matchingclosely with the probability of detection for a random search operation and verifying imperfect (albeit precise) detection.
The HBT platform increases the value of aerial surveillance operations with 98% efficacy in target elimination. Applying
coverage saturation with an accelerated intervention schedule to known patch locations is an adaptive process forcompensating imperfect detection and building intelligence with spatial and temporal relevance to the next operation.
Nomenclature: Miconia, Miconia calvescens DC.
Key words: Adaptive management, aerial surveillance, GIS, nascent patch network, random search operation,mortality factor.

An exotic plant invasion is a phenomenon carried out
by species with the capability to occupy niches alreadyinhabited by other indigenous or endemic plant commuDOI: 10.1614/IPSM-D-13-00059.1* First, third, and fifth authors: Assistant Specialist, Specialist andProfessor Department of Natural Resources and Environmental
Management, University of Hawaii at Manoa, Honolulu, HI 96822;
second, fourth, and sixth authors: GIS Specialist, Operations
Manager and ManagerMaui Invasive Species Committee, Universityof Hawaii at Manoa, Honolulu, HI 96822; seventh author: Director
Pacific Cooperative Studies Unit, University of Hawaii at Manoa,
Honolulu, HI 96822; eighth author, Liaison Pacific Islands Exotic
Plant Management Team, National Park Service Biological Resource
Management Division. Current address of first author: Maui
Agricultural Research Center, P.O. Box 269, Kula, HI 96790.
Corresponding author’s E-mail: leary@hawaii.edu

164

N

nities (Richardson et al. 2000). This invasion phenomenonis also a main driver in habitat fragmentation, leading tomodification of an ecosystem’s structure and function(Gilbert and Levine 2013). The resultant loss of endemic
biological diversity is particularly detrimental for isolatedisland ecosystems that exhibit high endemism (Denslow
2003; Mack et al. 2000; Reaser et al. 2007).
A commitment to weed species eradication starts with aneffective containment strategy targeting the nascent patch
network that is expanding the invasion front (Cousens
and Mortimer 1995; Moody and Mack 1988; Rejmánek
and Pitcairn 2002). Reconnaissance and surveillance arefundamental activities for nascent weed detection andspatial delimitation (Baxter and Possingham 2011; Cachoet al. 2007; Hester et al. 2010; Lawes and McAllister 2006;
Panetta and Lawes 2005; Rew et al. 2006; Taylor andHastings 2004). Reconnaissance tends to be a more cursory

Invasive Plant Science and Management 7, January–March 2014

Management Implications
The herbicide ballistic technology (HBT) platform is aherbicide delivery system registered as a 24(c) Special Local
Need for use in Hawaii to treat nascent satellite miconia patches inremote natural areas that require helicopter operations. We define
an intervention as a weed management operation with the
combined actions of target detection immediately followed byeffective elimination. In 14 mo, a total of 48 interventions wereconducted for seven nascent patches, (1) eliminating 4,029
miconia targets and (2) encompassing a total net area of
1,138 ha, while (3) administering , 1% of the maximum
allowable herbicide use rate. Target density reduction for the patch
network was . 86%, fitting an exponential decay function. This
resulted in a threefold improvement in search efficiency (min ha21)
and a 10-fold reduction in herbicide use rate (g ae ha21).
Expansion of the total net area corresponded to improvements insearch efficiency; less time was needed to saturate known target
locations with reduced densities. These interventions are describedas random search operations with imperfect detection. Efficacy ofan HBT application to miconia can be confirmed in less than
1 mo, allowing for the acceleration of intervention schedules thatcan compensate for imperfect detection by saturating coveragewith compounding sequential interventions. The goals of thisaccelerated intervention strategy are to rapidly reduce nascentpatch populations to manageable or undetectable levels and build
spatially and temporally explicit intelligence, where expected
projections are accurate with observed values.

process of searching for new target locations, whereas
surveillance is distinguished by a more intensive process ofbuilding explicit intelligence on known target locations
with repeated visits (Anonymous 2007). In the early stagesof strategy development, reconnaissance may be a necessary
trade-off to actual treatment activities when a lack ofintelligence compromises a sound priority decision process(Baxter and Possingham 2011). Otherwise, surveillance is amore common practice of gathering intelligence, usually as
an ad hoc activity complementary to active management
and relegated to within the immediate vicinity of the
management area (Cacho et al. 2007; Fox et al. 2009).
Detection of invasive plant species residing in their natural
settings is an imperfect process (Moore et al. 2011; Regan
et al. 2011). Good intelligence, regardless of the survey
design, should account for imperfect detectability as an
adaptive process for optimizing future operations (Moore
et al. 2011; Regan et al. 2011; Thompson 2002).
Cacho et al. (2007) coined the term ‘‘mortality factor’’ todescribe management of individual weed targets, accounting
for both detection and effective treatment as complementaryactions necessary to achieving target elimination. With aneffective treatment technique, detection then becomes thedeterminant outcome of an operation (Leary et al. 2013;
Lodge et al. 2006). Koopman (1946) introduced themathematical framework for estimating the probability ofdetection (Pd) in a random search operation that would be

expected within a terrestrial environment (Cooper et al.
2003). Search impediments (i.e., topography, weather,surrounding vegetation) imposing even slight randomness
in coverage (c), have been shown to fit the exponential
detection function (Equation 1) as a conservative estimate of
an imperfect search effort (Cacho et al 2007; Frost 1999):
pd ~1{e {c½1Herbicide Ballistic Technology (HBT) is a weed target
intervention platform that was developed in Hawaii toenhance helicopter surveillance operations with the capability to dispatch satellite weed targets upon detection (Learyet al. 2013). The HBT platform discretely administers smallaliquot herbicide projectiles through a pneumatic application device to treat individual weed targets with long-range
accuracy (i.e., 30 m [98 ft] effective range) from horizontal
or vertical trajectories. It expands the capability to treat all
detectable targets that might otherwise be untreatable withother conventional application methods. An effective HBTtreatment application enhances surveillance operations withthe full complement of a mortality factor (Leary et al. 2013).
The term ‘‘intervention’’ is used here to distinguish fromother surveillance operations with the inclusion of a mortality
factor accommodated by the integration of an HBTplatform. This study expands on platform calibrations
described by Leary et al. (2013) with the accelerated
deployment of an adaptive intervention strategy targetingthe primary nascent patch network of the miconia (Miconia
calvescens DC.) invasion in the East Maui Watershed (EMW;
Hawaii). We report on spatial and temporal parameters of
performance measures associated with patch target density
reductions incurred by these intervention sequences.
Materials and Methods

Target Species: Miconia calvescens. Miconia is a midstory
tree, 12 to 15 m tall, native to Central and South America.
It was introduced to the Hawaiian Islands in 1961 and waspresumably introduced to the island of Maui by 1970,
where the first management program in the state wasinitiated 20 yr later (Chimera et al. 2000; Medeiros et al.
1997). Miconia is an autogamous species that reaches
maturity in 4 to 5 yr. A single plant has immense fecundity,
producing millions of propagules in a single reproductive
cycle (Meyer 1998). Its fruit are small and edible, lending
itself to frugivorous dispersal by a diverse avian community(Chimera et al. 2000; Spotswood et al. 2013). In Australia,
the dispersal range of a nascent patch had been estimatedto exceed 2,000 m, but with 95% of the recruitment
contained within 500 m of the maternal source (Hardesty
et al. 2011; Murphy et al. 2008). Viable seed persistence
has been measured beyond 16 yr (Meyer et al. 2011),
contributing to the long-term recruitment potential of alatent seed bank.
Leary et al.: Reducing nascent miconia with HBT

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165

Over the last decade, systematic surveys of the entire
watershed have identified all major nascent patch populations along with hundreds of incipient satellites. Thesepatches are comparably smaller and phenologically distinguishable from the CORE, with plant maturity observed
less frequently. They are most often identified as juvenile
understory saplings (ca. , 3 m tall) that may be aggregating
into monotypic midstory canopies. These patches also tend
to colonize the extreme topography associated with theravines and drainages of EMW’s heterogeneous landscape(see Pouteau et al. 2011 for similar topographic features).

Figure 1. Map of East Maui Watershed with mean center ofthe miconia core infestation (CORE; black diamond) and thefinal net areas of the patch units (shaded buffers withcorresponding four-letter acronyms; black). See Experimental
Units in the Materials and Methods section. 300-m contours
displayed on the base map.

Suitable Habitat: The EMW. The EMW encompasses
over 55,000 ha (136,000 ac) on the windward slope of
Haleakala Crater on Maui. The core miconia infestation
occupies , 1,000 ha on the easternmost portion of EMW(20u479440N, 156u009520W), while the spatial distribution of the nascent patch network is spread across anestimated 20,000 ha (Figure 1). The invasion is below
1,000 m above sea level (masl) with invasion fronts
advancing south 8 km (5 mi) and west 18 km from thecore infestation (CORE), respectively. The mean annual
precipitation range within this area is 3,000 to 6,000 mm(118–236 in) (Giambelluca et al. 2013). The mean annual
temperature from Hana Airport (24 masl) is 23.4uC (74.1
F; 1950 to 2005; WRCC 2013) with a lapse rate of
20.64uC per 100 m elevation (Jacobson 2005). These
climatic conditions are consistent with the description of asuitable habitat in French Polynesia (Pouteau et al. 2011).
The dominant vegetation types include a wet coastal forest
with mixed exotic canopy species (e.g., African tulip tree
[Spathodea campanulata P. Beauv.], eucalyptus [Eucalyptus
robusta Sm.], guava [Psidium spp.]) that transitions to a wetmontane forest at higher elevations, represented byendemic assemblages (e.g. ohi’a [Metrosideros polymorpha
Gaudich] and koa [Acacia koa Gray]) (Wagner et al. 1999)
that also serve as critical habitat for 59 other threatened andendangered plant species (Anonymous 2000). Miconia iscapable of invading EMW critical habitat above 1,000 masl
(Medeiros et al. 1997; Meyer 1996; Meyer and Florence
1996; Pouteau et al. 2011), making mitigation of its spread
into these areas a strategic priority.
166

N

Experimental Units: The Miconia Patch Network. Sevenof the most prominent patches within the network wereselected to test an accelerated intervention schedule (seebelow): Nuuailua (NULU), Waiakuna Pond (WAKU),
Keanae Wall (KANE), Wailua nui (WALU), Wailua iki(WALI), Hanawi (HAWI), and Waihiumalu (WAHI)(Figure 1). Five of the patches (NULU, WAKU, KANE,
WALU, and WALI) were located along the western frontof the invasion, 12 to 18 km from the CORE. Each of thewestern-front patches was within a 1,000-m radius of thenext adjacent patch, creating a viable interpatch networkfor frugivorous dispersal (Hardesty et al. 2011; Murphy
et al. 2008). The HAWI patch was approximately 3,000 mfrom the nearest patch (WALI). However, several targets
interspersed between these patches had been dispatched inseparate operations that were not a part of this study. The
WAHI patch was located on the southern front of theinvasion and was closest to the CORE (ca. 8 km from
centers). One other known patch was just south of WAHI,
and was also being managed independently of this study.
The Accelerated Intervention Schedule. The strategy
implemented for this study consisted of an accelerated
deployment schedule of sequential interventions. A total of
48 interventions were conducted on eight separate dates
over a 14-mo period, with all patches receiving at least
four interventions and three of the seven receiving eightinterventions (Table 1). The time intervals between interventions ranged from 18 to 182 d with the median/modeinterval at 32 d. Based on previous recorded operations
conducted in these patch areas (2005 to 2011), theintervention schedules for this study were accelerated by
33% (Supplemental Table 1, http://dx.doi.org/10.1614/
IPSM-D-13-00059.TS1). All helicopter operations wereconducted with a full fuel load, providing 70 to 100 min ofoperation flight time. Starting locations were typically at thelowest elevation point for each patch, proceeding with anadaptive process of deliberating search efforts to known
target locations based on intelligence derived from previous
interventions (Fox et al. 2009; Thompson 2002). Anyremaining flight time would accommodate expansion of
search coverage to surrounding adjacent areas, typically intohigher elevations. Flight lines were anisotropic, running

Invasive Plant Science and Management 7, January–March 2014

Table 1. Intervention data recorded for the seven nascent miconia patches.
PatchInterventiona

Gross areab (ha)Net areac (ha)Targets

OFTd (min)

PCe

HAWI
WAHI
WAKU
WALI
WALU
NULU
KANE
NETWf

4
6
7
7
8
8
8
48

302.0
275.8
329.1
478.1
412.9
586.7
688.8
3073.4

130.8
94.4
194.0
175.0
154.4
174.6
214.9
1138.1

471
465
412
401
676
508
1096
4029

574.1
574.3
562.8
684.9
764.7
785.8
1169.85116.4

14,698
11,431
12,167
14,127
17,174
14,294
31,674
115,565aInterventions conducted in February 2012, May 2012, June 2012, October 2012, November 2012, December 2012, February
2013, March 2013, and April 2013.
b
Momentary gross area.
c
Cumulative net area.
dAbbreviations: OFT, operation flight time; PC, projectile consumption; HAWI), Hanawi; WAHI, Waihiumalu; WAKU,
Waiakuna Pond; WALI, Wailua iki; WALU, Wailua nui, NULU, Nuuailua; KANE, Keanae Wall; NETW, network.
e
Projectile consumption estimated from the pod inventory (ca. 140 projectiles pod21).
f
Total values for the entire patch network.

along the contours of the steep topography and with
iso-altitudinal transects spaced , 50 m of elevation apart for
ensuring visual search overlap from valley floor to ridgeline.
Helicopter HBT Platform and Intervention Procedures.
All aerial operations were conducted in a Hughes 500D
helicopter by a three-person crew with a portside bias
creating a 210u field of view and a detectable sight range
estimated at 50 m. Operation speeds were maintained at, 20 km h21 while actively searching. Miconia targets
were treated with 17.3-mm soft-gel projectiles encapsulating 199.4 mg ae (0.007 oz) of the active herbicide
ingredient triclopyr. Applicators administered three to fiveprojectiles to each stem axial point (e.g., larger targets withmore axial points received higher doses). The applicator,
seated portside behind the pilot, administered an effective
herbicide dose to target within a 30-m effective range.
Operation data were recorded with a FortrexH 301 global
positioning system (GPS) data logger (GarminH; Olathe,KS) with flight lines recorded as 5-sec vertex track logs anddispatched targets recorded as waypoints, which wereactually recorded from the position of the application andnot the actual location of the target (i.e., within 30 m). This
protocol was consistently applied to all recorded points due
to flight safety considerations. Projectile consumption wasdetermined at the end of each operation. For further details
on these protocols refer to Leary et al. (2013).
Geographic Information System Data Analyses. All GPS
data were projected in the NAD 1983 UTM Zone 4N
coordinate system and processed in ArcMAPH 10.1 (EsriH;
Redlands, CA). Tracks logs were manually spliced into
operation flight segments that were # 16 km h21. Searchcoverage areas were calculated from these operation flightsegments using buffer tool procedures with a full 50-m
radius and dissolved overlap. Operation times were
calculated by tabulating the number of vertices in thesesame flight segments (e.g., 12 vertices min21). All buffers
for each patch were superimposed with a union tool
procedure creating a field mosaic of the cumulative net
area. Coverage saturation levels for each field were scoredby the number of overlapping buffers. As an example, anarea mosaic created by eight interventions contained fields
representing all levels of saturation (i.e., 1 to 8). All target
waypoints were spatially joined to their respective buffer
unions for saturation field assignment.
Operation data sets consisted of (1) area, (2) time, (3)targets, and (4) projectile consumption, which were used to
calculate target density (targets ha21), search efficiency(min ha21), and herbicide use rate (g ae ha21). The dataand calculations were each assigned to three separate
subcategories:
1. momentary intervention assignment (momentary)—an
independent intervention data set with no saturation
field assignments, generating gross area and operation
performance values of the moment;
2. cumulative intervention assignment (cumulative)—acompilation of sequential data sets scaled by the numberof interventions with progressive assignments made to achanging saturation field mosaic, generating net area
and compounded operation performance values; and3. historic intervention assignment (historic)—all sequential data sets were retroactively assigned to the final
saturation field mosaic, generating gross area andoperation performance values for each momentary
operation in retrospect.
Leary et al.: Reducing nascent miconia with HBTN

167

Momentary data sets were used to calibrate searchefficiency and herbicide use rate corresponding to encountered target densities from independent flight segments (n 5103) contributing to the sequential interventions (n 5 48).
Cumulative data sets were used to calculate weighted meansaturation ( Csatn ) from the net area field mosaic with thesum of each (ith) saturation level adjusted by the respective
proportion of assignments, divided by the total field
assignments within the entire mosaic (Equation 2). In thisstudy, xi includes either area or target assignments with thehighest (ith) level of saturation equivalent to (n) interventions.
.X
Xn
xi
½2
Csatn ~ i~1 ðixi Þ
Cumulative target densities (Ctdn) were adjusted by dividing
the compounded values with their respective number (n)of contributing interventions (Equation 3). The influenceof sequential interventions on the adjusted target density was
fit with an exponential decay function for each patch(Equation 4).
Ctdn ~(Can =Ctn )=n½3

f (x)~yo e {ln½4Momentary and historic target densities only represent
outcomes of the moment, which is dependent on the area
searched and targets detected within that intervention.
Cumulative target densities, on the other hand, account fortargets dispatched in all previous interventions for the entire
net area, providing a more spatially accurate presentation ofprogress.
Detection efficacy (de), as described by Leary et al.
(2013), is the ratio of targets (x) recorded between
sequential interventions (n) spatially assigned to the same
saturation fields (Equation 5).
de~xn =xn zxnz1½5

Retroactive proportions of cumulative target and net
area totals (Cpropx) of each intervention were calculated
from the final total (Equation 6).
½6
Cpropx ~Cxn Cxfinal
Cumulative target proportions were plotted against theircorresponding coverage (c), which was calculated as theweighted mean net area saturation (Equation 4) multipliedby the cumulative net area proportion for each intervention(Equation 7).
c~ Csatn |Cpropn½7

Coverage of the last interventions (Cpropx 5 1) of eachpatch were equal to the highest weighted mean saturationlevels. These values were plotted with search theory
168

N

Figure 2. A scatter plot with best-fit lines and 95% confidence
intervals (dashed lines) for surveillance efficiency (dark circles;
min ha21; P , 0.001; R 2 5 0.78) and herbicide use rate (open
diamonds; g ae ha21; P , 0.001; R 2 5 0.91) corresponding toencountered target densities (targets ha21) derived frommomentary operation flight segments (n 5 103).

concepts postulating probabilities of detection (Pd) for arandom search operation (Equation 1) (Koopman 1946,
1980) and also a theoretically perfect ‘‘definite range’’
sensor (Equation 8) where Pd is proportional up tocomplete coverage (c 5 1), resulting in perfect detectionthat cannot be exceeded with added coverage:
Lim (Pd !c)
c?1

½8

Polynomial linear and two-parameter exponential decayfunctions were used to fit momentary and cumulative
sequential data plots, respectively, using SigmaPlotH(version 12.0, (Systat Software, Inc., San Jose CA).
Results

In a 14-mo period, starting in February 2012, a total of
48 interventions were administered to the seven patches,covering 1138.1 net ha and dispatching 4,029 targets(Table 1). In total, 5,116.4 min of operation flight time(ca. 85.3 h) and 115,565 projectiles were utilized toaccomplish these results. HAWI was the last patch on
which the accelerated strategy was initiated and it wasadministered only four interventions, whereas WALU,
NULU, and KANE were administered twice as many.
Except for WAHI, all patch net areas were . 100 ha, with
KANE being the largest at 214.9 ha, which also recorded
the highest number of dispatched targets (i.e., 1,096
targets). Effective applications of previous interventions
were visually confirmed even for the shortest time interval(i.e. 18 d). Only 88 survivors were retreated, indicating
98% efficacy with the HBT platform (data not shown).
Linear fits for search efficiency and herbicide use rate
were highly significant when plotted against target densities

Invasive Plant Science and Management 7, January–March 2014

Figure 3. Adjusted cumulative target densities (targets ha21; solid black lines) of each patch and the entire network (6 SE; n 5 7 for
one to four interventions; n 5 6 for five or six interventions; n 5 5 for seven interventions and n 5 3 for eight interventions) with best-fit
exponential decay functions (black dot-dash lines; P , 0.05; R 2 . 0.88). Notice KANE with a larger target density scale on the y-axis.

encountered (P , 0.001; n 5 103) (Fig. 2). Searchefficiency was measured at 0.90 min ha21, dispatch time at
0.53 min target21, and herbicide dose was estimated at 32
projectiles target21. All herbicide use rates were , 1% of
the maximum allowable rate (i.e. 672.0 g ae ha21). The
high coefficients of determination illustrated a strong
dependence to target density, and validated platform
consistency with previously published results (Leary et al.
2013), despite the use of multiple pilot/applicator teams
across seven different sites.
All patches displayed reductions in cumulative target
densities (adjusted by the number of interventions),
following their respective intervention sequences. All
reductions were significantly fit to exponential decayfunctions (P , 0.05; R 2 . 0.88; coefficient of variation
for the root mean square residuals between observed andfitted values , 0.393) despite the variability of initial target
densities (1.4 to 7.0 target ha21) and intervention sequences(four to eight interventions) (Figure 3; Table 2). Two
general observations were made: (1) the sharpest reductions
in target density occurred within the first three interventionsand (2) targets were dispatched in every operation. Similar
reductions were also observed for momentary target density
sequences, but with greater peak deviations from the best-fit
decay functions (data not shown). Cumulative target
densities are comprehensive values of the entire patch, with
reduction observed when target density of the lastintervention was less than the net value of all previous
interventions. These decay functions were influenced by adiminishing number of targets recorded in the latterinterventions, with the curve asymptotically approachingzero, which will continue even beyond the point of
eventually recording momentary undetectable levels.
Mean momentary search efficiency and herbicide use
rate were reduced with each sequential intervention,corresponding to lower target densities encountered(Figure 4). Search efficiency is optimized when no targets
are detected (Leary et al. 2013). As target density reduced
to , 1 target ha21 (i.e., operations 7 and 8), mean searchefficiency was approximate to the calculated y-intercept
coefficient (see Figure 2), suggesting some discrepancy
between these independent derivations. Herbicide use rate
showed a similar reduction trend with the final mean value
equivalent to 0.06% of the maximum allowable use rate.
Thus, the efficacy of previous interventions contributed to
improved performance efficiencies for subsequent interventions on these accelerated schedules.
Mean net area increased with every sequential operation(Figure 5). This is due in part to improved searchefficiencies making operational flight time available for
expanding area coverage (see Figure 4). Net area expansion
influenced the exponential decay of the cumulative target
densities, with fewer targets being dispatched in thesesurrounding areas.
Leary et al.: Reducing nascent miconia with HBT

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169

Table 2. Parameters of the exponential decay function estimated for each patch.
Patch

TDia,b (targets ha21)

lc

Pd

R2

CV(RMSR)TDf (targets ha21)

HAWI
WAHI
WAKU
WALI
WALU
NULU
KANE
NETWe

4.5
3.4
5.0
1.4
3.0
3.0
7.0
3.9 6 0.2

0.808
0.322
1.170
0.286
0.239
0.434
0.488
0.476

0.041
0.003
0.001
, 0.001, 0.001
0.003, 0.001, 0.001

0.92
0.91
0.89
0.96
0.90
0.90
0.95
0.94

0.222
0.165
0.392
0.113
0.176
0.259
0.215
0.229

0.9
0.8
0.3
0.3
0.5
0.4
0.6
0.5 6 0.1aAbbreviations: TD, target density; CV(RMSR), coefficient of variation for the root mean square residuals between observed and fitted
values; TDf, final adjusted cumulative target densities; HAWI, Hanawi; WAHI, Waihiumalu; WAKU, Waiakuna Pond; WALI,
Wailua iki; WALU, Wailua nui, NULU, Nuuailua; KANE, Keanae Wall; NETW, network.
b
Initial adjusted cumulative target densities.
c
Decay function exponent.
d
P value for nonlinear regression.
e
The mean TDi–f 6 SE of the entire patch network with the other calculations based the best-fit exponential decay curve.

Mean saturation for net area and target assignments
increased with each sequential operation (Figure 6). The
positive trends are an indication of the strategy’s adaptive
quality for revisiting known target locations. The rate of
cumulative target saturation advanced nearly three times
faster than net area saturation as determined by slope
coefficients of best-fit linear models (P , 0.001, R 2 .
0.98; data not shown). Cumulative target saturation was
influenced by progressive reassignment of former dispatched targets to their next level of saturation, along with

Figure 4. Mean search efficiencies (dark triangle) and herbicide
use rates (light diamond) derived from momentary interventions(6 SE; n 5 7 for one to four interventions; n 5 6 for five or six
interventions; n 5 5 for seven interventions and n 5 3 for eightinterventions) with mean momentary target density serving as a
backdrop for each sequential operation. Backdrops appear
oversized and transparent for the sole purpose of referencing
target densities to the intervention performance values in focus
and do not constitute any variance or deviation of the mean.

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continued detection of new targets in these same saturated
fields. Net area saturation was influenced by the same
adaptive paradigm of saturation reassignment, and was
also counter influenced by net area expansions with new
unsaturated fields where less targets were detected, as statedabove (see Figure 4).
Distinct differences in saturation field assignments wereobserved between final net areas and historic target points
were distinct for all patches (Figures 7 and 8). Net area
assignments were overrepresented by the lowest saturationlevel, whereas historic target assignments were overrepresented by the highest saturation levels. For instance, theexpanded area for the entire patch network was almost six
times larger than the highest saturation levels of each patch
combined. By comparison, historic target assignments in

Figure 5. Mean cumulative net areas of sequential interventions(6 SE; n 5 7 for one to four interventions; n 5 6 for five or six
interventions; n 5 5 for seven interventions and n 5 3 for eightinterventions).

Invasive Plant Science and Management 7, January–March 2014

Figure 6. Weighted mean saturation for cumulative target(dark squares) and net area (light circles) field mosaic
assignments (6 SE; n 5 7 for one to four interventions; n 5
6 for five or six interventions; n 5 5 for seven interventions andn 5 3 for eight interventions).

the highest saturation levels were 20 times greater than total
representation in the lowest saturation level. In practicalterms, this highlights the basic elements of an adaptive
surveillance process for delimiting satellite populations
by continuing to revisit known target locations as long as
new targets are being detected, while also progressively
expanding surveillance coverage into new territories wherefinding targets is a more anomalous occasion.
As an example, Figure 9 shows the spatial dynamics ofthe sequential interventions imposed on the KANE patch.
Similar to all of the other patches, this adaptive sequence
depicts (1) target reduction and (2) net area expansion andincreased complexity of the saturation field mosaic. Also,target detections are recorded throughout the net area, butwith a majority of targets consistently recorded in thehighest-saturation fields.

Figure 8. Proportion of historical target assignments to thefinal saturation field mosaic of each patch. NETW represents the
proportion of the total assignments for all seven patches.

Mean detection efficacy of all interventions ranged from0.56 to 0.76 (Figure 10). The phenomenon of imperfectdetection is likely the artifact of two conditions: (1) false
negative (type II) error with a failure to detect or (2)biological recruitment of target individuals achieving
stature that exceeds the threshold of detectability. Mean
detection efficacy of the entire patch network was 0.62 6
0.3, which is conspicuously close to the probability ofdetection (Pd) of a random search operation (i.e. 0.63)
where coverage (c) equals 1 (Koopman 1946, 1980).
Detection efficacy, as measured in this study, is anempirical value between sequential interventions where
coverage of the overlapped field is equal to 1. Cumulative
target proportions (n 5 41) plotted against theircorresponding coverage values also fit closely with theexponential detection function for a random search
operation (Figure 11).
Discussion

Figure 7. Proportion of the final cumulative net area
assignments to the saturation field mosaic of each patch. NETW
represents the proportion of the total assignments for allseven patches.

Miconia has been naturalizing in the EMW for over
40 yr, with the extant of the invasion approaching
20,000 ha, making containment the current management
goal (Duncan and Leary 2013). Over the last two decades,
fluctuations in funding have guided management decisions.
Efforts to reduce high-density infestations have beenprioritized in well-funded years, although more often thepriority is to focus efforts on reducing low-density nascentfoci (Taylor and Hastings 2004). The HBT platform is
specifically designed for treating individual weed targets,and is ideal for administering interventions to low-density
patch populations. Adoption of this technology has
invigorated the miconia containment strategy with accelerated interventions measurably reducing the nascent patch
network within a short period of time. In the 14-mo period
reported here, operations increased by 33% over the
average number of operations (per 14 mo) conducted for
Leary et al.: Reducing nascent miconia with HBTN

171

Figure 9. Intervention sequence (1 to 8) for KANE patch showing targets dispatched (white circles) and the net area field mosaic with increasinglevels of saturation (yellow-to-red). Targets (T) and area (A) are presented (momentary/cumulative) along with weighted mean saturation levels
shown in parentheses. 30-m contours displayed on the base map. (Color for this figure is available in the online version of this paper.)

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Invasive Plant Science and Management 7, January–March 2014

Figure 10. Mean detection efficacy (6 SD; n 5 no. ofinterventions 2 1; refer to Table 1) of each patch including theentire patch network (NETW; mean of all patches 6 SE, n 5 7).

the entire patch network from 2005 to 2011. Consequently,
the number of targets eliminated increased by 168%
(Supplemental Table 1, http://dx.doi.org/10.1614/IPSM-D13-00059.TS1). It is worth reiterating that these patch
networks are in remote areas, accessible only to aerial
operations. In these cases, the HBT platform improves target
accessibility with capabilities in delivering an effective
herbicide dose with horizontal trajectory and long range
accuracy, relative to current aerial treatment options that mustline up directly over the target (e.g., long line sprayer). We arealso continuing to validate high treatment efficacy of HBT. In
reference to the mortality factor, the HBT platform provides
assurance that detectability is the limiting factor (Leary et al.
2013). This study shows how detectability can be improvedby accelerating the intervention schedule. Eventually, future
operations will begin recording momentary undetectabletarget levels with intermittent detection of recruitment events
leading to exhaustion of a latent seed bank.
The entire spatial distribution of a weed invasion must
be properly delimited to ensure effective containment(Panetta and Lawes 2005). The surveillance/intervention
approach used in this study shares some of the qualities
for a delimiting process described by Leung et al. (2010),
in which they highlight the (1) approach, (2) decline, and (3)delimitation of a patch as an inside-out tactic for determining
an effective containment boundary. All of the patches in thisstudy are in the ‘‘decline’’ stage, where the least number oftargets are assigned to the lowest-saturation fields (Figure 8),
which also tend to be spatially located on the peripheries of
the respective net area mosaics (see Figure 9). This strategy
will not proceed to the ‘‘delimit’’ stage until all targets havebeen assigned to multi-saturated fields and net area has
expanded beyond the most distal target assignments.
The detection efficacies recorded for these interventions
fit the description of a random search operation (Cooper
et al. 2003). A theoretically perfect search of a ‘‘definite
range’’ sensor detects 100% of all targets with complete

Figure 11. Sequential cumulative target proportions (n 5 48)
plotted against their respective weighted mean saturation values,
along with Pd of a theoretical ‘‘definite range’’ sensor (solid blackline; Equation 8) and a random search operation (black dot-dash;
Equation 1) (Koopman 1946, 1980).

uniform coverage, making any further investment in search
effort a waste of resources (Koopman 1946, 1980).
However, any randomness in a search effort will reduce Pd(Cacho et al. 2006, 2007; Cooper et al. 2003; Frost 1999).
In fact, for a random search operation, it would take threesuccessive interventions with no detections recorded in order
to assume a high probability of 0.98 that no targets are in thearea. Only two of the seven patches have a final coverage. 3.0 in this study. However, targets continued to berecorded up to the last intervention, which strongly suggests
the possibility of target recruitment taking place during thecourse of this study. This is further supported by a significant
linear decline in detection efficacy from 18 to 182 d between
interventions (P , 0.039, R 2 5 0.127; data not shown),suggesting a greater possibility of new recruitment withlonger time intervals. With the combination of imperfectdetection and active recruitment, future interventions thatrecord undetectable levels should not serve as absoluteconfirmation of population extirpation. However, it does
provide the opportunity to more accurately record intermittent detections as intrapatch recruitment (i.e., spatiallyassigned to high-saturation fields) or stochastic dispersal
events (i.e., spatially assigned to low-saturation fields).
In a weed management scenario, randomness resulting
in type II errors might include (1) physical stature of aplant target, (2) spatial arrangement of cohorts within thelandscape, or (3) search capability (Cacho et al. 2004).
Individual miconia targets can grow . 1 m in height in
1 yr, reaching a detectable threshold within that time
period. Thus, what was undetectable in the previous
interventions will eventually become detectable in subsequent interventions. These patch populations tend to bewell hidden in topographic drainages and ravines as anunderstory to a complex forest canopy structure, creating
impediments to clear sight lines. As a frugivore-dispersed
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propagule, miconia targets have been commonly found hiding behind the trunks of canopy trees that have presumably
served as bird defecation perches. The helicopter operations
performed in these extreme three-dimensional spaces are also
likely incurring randomness during the search effort. The
operation flight lines are not perfectly spaced parallel tracks ona two-dimensional plane (as in ocean search and rescue), butinstead are anisotropic to the terrestrial landscape with intent
by the pilot to overlap the fields of view for each track withaltimeter adjustments and visual cues in the landscape. The
exponential detection function (Pd) is solely dependent on theamount of search effort applied uniformly to an area,
regardless of whether it is applied all at once or incrementally(Koopman, 1946, 1980). Admittedly, the adaptive approachto saturating coverage in known target locations is not a
uniform process, yet net coverage derived from the weighted
mean saturation values still show good correspondence to the
Pd of a random search operation. Furthermore, if recruitment
and growth to detectable target size is actively occurring, total
search effort applied to a single intervention would likely be
ineffective. The early development of herbicide symptoms on
miconia was critical to distinguishing new (untreated) targets
in subsequent interventions. This feature alone allowed for theacceleration of intervention deployments, leading to anincreased probability of target detection in rapid succession.
In this study, there are three potential outcomes to anintervention:
1. expansion—initial area coverage naive to any target
encounters, which could be the first operation or asubsequent, sequential operation expanding beyond
known target locations;
2. saturation—sequential interventions covering known locations with measurable reductions in target detection; or
3. confirmation—the final sequence of interventions monitoring momentary undetectable target levels with thelikelihood of intermittent detections characterized as
recruitment events, particularly in known target locations.
As the net area surveyed for each patch continues toexpand, major portions of the network will amalgamate into a
contiguous and complex saturation field mosaic. Continuing
to build on this intelligence will provide clear depictions ofactive target locations surrounded by confirmed protectedareas. The fit of empirical target values to exponential decay
and detection functions prove that this accelerated intervention strategy is outpacing the biological recruitment of thishighly invasive species. As progress continues, new strategies
will lead to a deceleration of interventions and a refinement ofcoverage, optimizing future operations within the frameworkof an efficient, long-term containment strategy.
Acknowledgments

This project was funded in parts by U.S. Department ofAgriculture (USDA) Forest Service, Special Technology
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Development Program Award R5-2012-01 through a collaboration with the Hawaii Department of Land and Natural
Resources Forest Health Program, the USDA Hatch Act
Formula Grant project 112H, and Maui County Offices of
Economic Development and Department of Water Supply.
The USDA, the State of Hawaii, and the County of Maui areequal opportunity providers and employers. We would also
like to give our special appreciation to Mr. Chuck Chimera
for his editorial improvements and local expertise. The
authors claim no conflict of interest in this report.

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Invasive Plant Science and Management 2013 6:292–303

Calibration of an Herbicide Ballistic
Technology (HBT) Helicopter Platform
Targeting Miconia calvescens in Hawaii
James J. K. Leary, Jeremy Gooding, John Chapman, Adam Radford, Brooke Mahnken, and Linda J. Cox*
Miconia (Miconia calvescens DC.) is a tropical tree species from South and Central America that is a highly invasivecolonizer of Hawaii’s forested watersheds. Elimination of satellite populations is critical to an effective containment
strategy, but extreme topography limits accessibility to remote populations by helicopter operations only. Herbicide
Ballistic Technology (HBT) is a novel weed control tool designed to pneumatically deliver encapsulated herbicide
projectiles. It is capable of accurately treating miconia satellites within a 30 m range in either horizontal or verticaltrajectories. Efficacy was examined for the encapsulated herbicide projectiles, each containing 199.4 mg ae triclopyr,
when applied to miconia in 5-unit increments. Experimental calibrations of the HBT platform were recorded on a
Hughes 500-D helicopter while conducting surveillance operations from November 2010 through October 2011 on
the islands of Maui and Kauai. Search efficiency (min ha21; n 5 13, R2 5 0.933, P, 0.001) and target acquisition
rate (plants hr21, n 5 13, R2 5 0.926, P, 0.001) displayed positive linear and logarithmic relationships,
respectively, to plant target density. The search efficiency equation estimated target acquisition time at 25.1 sec and aminimum surveillance rate of 67.8 s ha21 when no targets were detected. The maximum target acquisition rate for
the HBT platform was estimated at 143 targets hr21. An average mortality factor of 0.542 was derived from theproduct of detection efficacy (0.560) and operational treatment efficacy (0.972) in overlapping buffer areas
generated from repeated flight segments (n 5 5). This population reduction value was used in simulation models toestimate the expected costs for one- and multi-year satellite population control strategies for qualifying options incost optimization and risk aversion. This is a first report on the performance of an HBT helicopter platform
demonstrating the capability for immediate, rapid-response control of new satellite plant detections, while
conducting aerial surveillance of incipient miconia populations.
Nomenclature: Miconia, Miconia calvescens DC. MICA20.
Key words: Hawaii, Herbicide Ballistic Technology.

The loss of endemic biological diversity due to exotic
plant invasions is particularly detrimental on isolatedislands (Denslow 2003; Mack et al. 2000; Reaser et al.
2007). Either eradication or containment of the invasive
species can serve as viable mitigation strategies dependingon which option has the greatest potential for success
DOI: 10.1614/IPSM-D-12-00026.1* First and sixth authors: Assistant Specialist and Specialist,
Department of Natural Resources and Environmental Management,
University of Hawaii at Manoa, PO Box 269, Kula, HI 96790;
second author: Liaison, Pacific Islands Exotic Plant Management
Team, National Park Service, PO Box 880896 Pukalani, HI 96788;
third author: Operations Planner/Analyst, Kauai Invasive Species
Committee, P.O. Box 1998, Lihue, HI 96766; fourth and fifth
authors: Operations Manager and GIS Specialist, Maui Invasive
Species Committee, P.O. Box 983 Makawao, HI 96768. Correspondending author’s Email: leary@hawaii.edu

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Invasive Plant Science and Management 6, April–June 2013

(Panetta 2009; Panetta and Cacho 2012; Taylor andHastings 2004; Wittenberg and Cock 2001). Regardless of
the approach, detection and control must be effectively
applied to the entire population, particularly with the mostisolated satellites (Brooks et al. 2009; Cacho et al. 2006;
Hulme 2006; Myers et al. 2000; Panetta 2009; Panetta andLawes 2005). Archiving knowledge of the target species isalso critical to determine the management approach andwould include studies on the biology (e.g. growth andfecundity), ecology (i.e. propagule dispersal) and physiography (i.e. suitable habitat) of the target species (Chimera etal. 2000; Florence 1993; Hardesty et al. 2011; Kuefer et al.
2010; Pouteau et al. 2011). An effective species mitigation
strategy combines (1) practical knowledge, (2) sustained
resources and (3) proven actions that progress towards ameasurable reduction of target density and contraction of
the delimited invasion perimeter.

Management Implications
Herbicide Ballistic Technology (HBT) is a novel application
technique designed to deliver encapsulated herbicide projectiles
with long-range accuracy and precision. We report on theperformance of an HBT platform providing immediate controlof miconia (Miconia calvescens DC.) satellite plants, detected while
conducting helicopter surveillance calibrations in Hawaii’s remote watersheds. Flight calibrations (n 5 13) generated efficiency
parameters related to the functionality of the platform. Plant target
density was a significant variable for determining search efficiency(min ha21), target acquisition rate (plants hr21) and herbicide use(g ae ha21). The product of detection efficacy and treatment
efficacy estimated population mortality (i.e. reduction) as another operational parameter used in simulation models to project
feasibility and expected cost of different population reduction
strategies based on cost optimization and risk aversion. This
research is critical to our technology transfer program that includes
development of the standard operating procedure for safe use of
the HBT platform, which has been approved by the PacificCooperative Studies Unit, University of Hawaii and approval by
the Hawaii Department of Agriculture for a FIFRA Section 24c
Special Local Needs registration for HBT-G4U200 with GarlonH
4 Ultra (EPA SLN Reg. No. HI-120001), with miconia listed as atarget species.

Miconia (Miconia calvescens DC.) is a mid-story tree, 12
to 15 m tall, native to Central and South America. It haslarge, bicolored leaves that are up to 80 cm in length, which
made this species desirable to botanical hobbyists andhorticultural professionals. This led to purposeful introductions to other suitable habitats throughout the Pacific(Meyer 1996). It is currently listed as one of the 100 worst
global invasive species (Lowe et al. 2000), is a class 1 weedin Queensland, Australia (Hardesty 2011) and a statenoxious weed in Hawaii, USA (Medeiros et al. 1997). The
miconia infestation in Tahiti has been well characterized.
After its introduction in 1937, it became the dominant
vegetation to over 65% of the forest in less than 60 yr(Florence 1993; Meyer 1996). High densities of thisshallow rooted species are known to shade out theunderstory vegetation and further suspected to promotesoil surface erosion, particularly on steeper terrain(Giambelluca et al. 2010; Medeiros et al. 1997; Meyer
1996).
Miconia is an autogamous species that reaches maturityin 4 to 5 yr. A single plant has immense fecundity, with theability to produce millions of propagules in a single
reproductive cycle (Meyer 1998). Miconia produces asmall, edible fruit, approximately 5.9 mm in diam (0.23 in)lending itself to frugivorous dispersal by a generalist avian
population (Chimera et al. 2000). In Australia, both
Hardesty et al. (2011) and Murphy et al. (2008) infer that
95% of dispersal events occur within 500 m, but with amaximum dispersal range that could go beyond 2000 m.
The current recommendation is for maintaining radialmanagement buffers that are at least 500 m, but preferably
1000 m (Hardesty et al. 2011). The most recent reportfrom Tahiti has validated seed bank viability to be over
16 yr (Meyer et al. 2011). Thus, preventing satellite
miconia populations from reaching maturity (i.e. elimination) is critical to mitigating the invasion.
Miconia was introduced to the Hawaiian Islands in 1961
(Medeiros et al. 1997). Thirty years later, the firstmanagement program was initiated on Maui and by
1996 management programs existed on the islands ofKauai, Oahu and Hawaii (Chimera et al. 2000).
Population reduction (i.e. containment over eradication)
was recently determined to be the optimal management
policy for minimizing expected costs of control on Oahu,
Maui and Hawaii. On Kauai, deferment of control was
suggested due to the higher costs associated with searchingin a much lower population density, (Burnett et al. 2007).
Currently however, all islands, including Kauai, areoperating under a more risk averse policy that implements
surveillance and treatment operations focused on known
incipient populations. This approach may have higher
operational costs, but also presents greater opportunity to
mitigate detrimental uncertainties regarding the extent ofthese invasions. Reduction of satellite populations can havea more mitigating effect on an invasion compared tocontrol efforts in a higher density core infestation (Moody
and Mack 1988). Search effort, particularly in remotenatural settings, is a costly procedure, making plant
detectability critical to effective containment (Cacho etal. 2007; Hester et al. 2010). Costs are further compounded when plant detection and treatment activities are
performed in separate operations, which has often been
the case for controlling miconia in Hawaii.
The herbicide active ingredient triclopyr is lethal tomiconia in low doses as basal bark or foliar applications(Chimera et al. 2000; Medeiros et al. 1998). The aerial
long line spray system currently used to treat miconia, wasoriginally developed by the US Drug Enforcement Agency
for marijuana (Cannabis sativa L.) control. A typicalassembly consists of a 95 L tank (25 gal) mounted to thecargo hook of a Hughes 500-D helicopter and a tethered
30 m by 9 mm hose with a distal nozzle configuration for
directed applications administered by the pilot. Most aerial
operations are relegated to inaccessible locations and often
require separate reconnaissance and treatment flights due toencumbrance of the long line sprayer (Burnett et al. 2007).
This spray system relies on pilot dexterity to safely position
the nozzle assembly directly overhead, and is typicallylimited to treating miconia in open tree canopy gaps andon shallow slopes. However, miconia is also able to resideon much steeper slopes up to 75u (Pouteau et al. 2011) andunder impeding tree canopy (Meyer 1994), making it
difficult or impossible for the long line sprayer to treat all
targets. This limitation ultimately compromises the success

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of an effective containment strategy (Myers et al. 2000,
Panetta 2009).
Herbicide Ballistic Technology (HBT) is a novel
herbicide delivery technique designed to discretely administer encapsulated herbicide aliquots through a pneumatic
device to individual weed satellites with long-range
accuracy. The effective treatment range is 30 m in either
horizontal or downward vertical trajectories, while maintaining submeter accuracy. The high velocity impact of the
projectile to the plant (ca. 50 m s21) creates a circularspatter pattern that is approximately 1 m2, with ourobservation that a majority of the fluid is retained at the
point of impact. This precision delivery platform is
uniquely suited to treating satellite miconia residing on
extreme topography or under tree canopy that would
otherwise impede the long line sprayer.
The objectives of this study were to determine triclopyr
efficacy when delivered as HBT projectiles to miconia andevaluate the utility of an HBT aerial platform in helicopter
surveillance calibrations. The empirical performance measures were further utilized in model simulations withexpected cost analyses to project effective containment
strategies of incipient miconia populations.
Materials and Methods

The HBT Projectile. Batch processing of HBT projectiles
was conducted by the Nelson Paint Company (EPA Est.
No. 86199-MI-001) using standard in-house proceduresfor producing spherical soft gelatin capsules (17.3 mm dia.)with a 2.6 ml (0.09 fl. oz) liquid fill capacity. The HBTTCP200 herbicide formulation is a simple bipartite blendof triclopyr (3,5,6,-trichloro-2-pyridinyloxyacetic acid,butoxyethyl ester; GarlonH 4 Ultra, EPA Reg. No. 62719527, DowH Agrosciences LLC Indianapolis, IN) diluted
with a modified vegetable oil concoction of surfactants andcoupling agents to produce a projectile unit with 199.4 mg
ae. The HBT-IMZ31 herbicide formulation is imazapyr(2-[4,5-dihydro-4-methyl-4-(1-methylethyl)-5-oxo-1Himidazol-2-yl]-3-pyridinecarboxylic acid; ArsenalH PowerlineTM, EPA Reg. No. 241-431, BASFH Corp., Triangle
Park, NC) blended with the same adjuvant concoction to
produce a projectile unit with 31.2 mg ae. HBT-TCP200
and HBT-IMZ31 formulations are comparable to 16%
and 5% v/v, respectively.
Treatment Efficacy Validation. Two ground-based fieldtrials were established in February 2010 to compare efficacyof the HBT-TCP200 and HBT-IMZ31 on miconia within
the East Maui infestation (20u459460N, 156u019170W).
The first experiment was conducted as a completely
randomized design replicated three times with a 2 by 2
factorial treatment set comparing formulations (TCP200
vs. IMZ31) at two different application rates (5-unit vs. 10294

N

Invasive Plant Science and Management 6, April–June 2013unit). All experimental targets were juvenile miconia ofrelatively uniform size with a single leader stem between 3
to 5 m tall. Projectiles were administered at the lowest axial
point from a 3 m range with a marker calibrated todischarge a projectile with a 100 m s21 muzzle velocity. A
second experiment compared the formulations as a 5-unit
application rate targeting the base of the main leader stem
approximately 30 cm from the soil surface. Visualconfirmation of treatment lethality was conducted in
September 2010 (227 DAT).
The Onboard HBT Platform. The three basic components of the onboard HBT platform include: (1) the HBT
projectile inventory subdivided into pods (ca. 140
projectiles) serving as retention devices during transfer tothe (2) electro-pneumatic application marker (BTH
TM7TM, Kee Action Sports LLC, Sewell, NJ) consistingof a microswitch-controlled solenoid actuating a 1380 kPa
compressed air discharge for bolt-action propulsionof3
projectiles powered by (3) a regulated 1180 cm aluminum
reservoir tank pressurized up to 20,700 kPa. The marker
was calibrated to launch projectiles through a 30 cm long,ceramic-coated, smooth bore barrel calibrated for a muzzle
velocity of 100 m s21 and a terminal range of just beyond
50 m. The tanks were connected to the marker via coiled
high pressure remote line with quick connect coupler andsliding check valve for depressurized tank replacement. The
complete onboard assembly consisted of forty pods (ca.
5,600 units), six tanks, and two markers. The platform wasdesigned to match resource consumption (i.e. projectiles
and compressed air) with operational flight time (ca.
100 min) and accommodate redundancy in the event of aminor component malfunction.
HBT Calibration Flight Segments and Site Locations.
HBT platform calibrations were derived from flightsegments of helicopter surveillance operations that weredistinguished by date, time and site. Up to two segments
were recorded from a single operation, although mostoperations had only one segment recorded. A total of
thirteen calibration flight segments were recorded from
October 2010 to November 2011 in three sites on theisland of Maui: Wailua Nui (20u509060N, 156u089060W,
three flight segments); Waiokamilo (20u509030N,
156u089280W, two sites with three flight segments each),and one site on the Island of Kauai: Opaekaa (22u049500N,
159u249110W, four flight segments).
In-flight HBT Calibration Protocols and Recorded
Parameters. All calibrations were conducted onboard a
Hughes 500-D helicopter with doors removed and a threeperson crew configured with the applicator seated portside,
posterior to the pilot and an additional spotter seated in thefront, starboard side. All crewmembers were responsible forsafety monitoring and miconia target detection. The targetportions. Pod (ca. 140 projectiles) inventory consumption
was recorded for each flight segment.

Figure 1. An HBT operator positioned in the portside rear seatof a Hughes 500-D with a pneumatic device engaging two
incipient miconia targets within effective range and a clear line ofsight. Photo credit to Josh Atwood.

acquisition process between the pilot and the applicator
was initiated by positive identification of the miconia target
followed by the aircraft safely approaching to within a 30 m
range and clear line of sight (PCSU 2011; see Figure 1). A
target window was designated for the applicator to safely
discharge projectiles within a 270u to 300uhorizontal
trajectory (i.e. 9 to 10 o’clock position) and a 200u to
270u vertical trajectory (i.e. landing skid to eye level). With
the aircraft in a stationary position, the applicator obtained
permission from the pilot to treat the target, discharged
projectiles, recorded GPS waypoint and cued the pilot tocontinue with the operation. Detection from the helicopter
was typically limited to miconia plants that were at least
1 m tall with fully expanded leaves (i.e. assumed to be atleast 2nd-yr juveniles). All applications were administeredas a 5-unit treatment to each visible axial point of the plant.
Juvenile plants were supported by a single leader stem that
could range from 1 to 4 m tall and typically had , 5 axial
points, while larger (potentially mature) plants would
display a spreading canopy with $ 5 axial points. All planttarget waypoints and corresponding logs of the flight path
were recorded with a GPS device (ForetrexH 301; GarminH
Olathe, KS) set to record geographical position, timestampand velocity on 30-s intervals. Discrepancy between therecorded applicator location and the actual offset distanceof the target should be noted. In most cases, closely
approaching the target would have been hazardous or
impractical and would also have confounded the timeparameter of the calibration. All of the targets were locatedwithin 30 m of the recorded waypoint. Survivors of earlier
treatments were also recorded for repeat calibrations andwere identified as symptomatic targets with viable intact
canopy and were administered retreatment to those living

Platform Performance Calculations. Operational flightsegments containing first and last recorded miconia targets
were spliced from raw track logs by removing the ferry
portions (determined by flight segments to and from thelanding zone that exceeded 20 km hr21) using MapsourceH(version 6.12.4; GarminH Olathe, KS). Net surveillanceareas were calculated with a 50 m buffer on each side of
the operational flight segments with overlapped portions
dissolved using the buffer analysis tool in ArcGISH (version
10.0; ESRIH Redlands, CA). The time interval between thetimestamps of the start and end points were recorded. Plant
target density was the product of targets acquired divided
by the segment area, reported as targets ha21. Target
acquisition rate was the product of the targets acquired
divided by the segment time, reported as targets hr21.
Search efficiency was the product of segment time divided
by segment area, reported as min ha21. Detection efficacy
was based on the assumption that all targets acquired in thesubsequent overlapping segment were not detected in theprevious segment and was calculated as the product oftargets acquired in the previous segment divided by thecomposite of all targets acquired in the previous andsubsequent segments. This is a conservative, but reasonableassumption that newly recorded miconia targets is more
likely the result of crew detection errors in the previous
operation than actual recruitment within the short timeintervals between flight segments (i.e. 89 to 171 days).
Operational treatment efficacy was the product ofeffectively treated targets divided by the total targets
acquired. Effectively treated targets were deciphered bysubtracting the number of survivors identified in thesubsequent segment. Mortality factor as described by Cachoet al. (2007) is the product of the probability of detection
multiplied by treatment efficacy. For this study, themortality factor was empirically derived as the product ofdetection efficacy multiplied by operational treatment
efficacy calculated from the repeated overlap areas. Target
herbicide dose was calculated as the product of pod
inventory consumption divided by the targets acquired ina flight segment. Similarly, herbicide use was calculated as
the product of pod inventory consumption divided by the
buffered surveillance area. Both projectile consumption
parameters were reported in triclopyr acid equivalents basedon a known quantity of each projectile (e.g. 199.4 mg ae).
Simulation Models and Expected Cost Analyses. Simulations of 1-yr population reduction strategies withinbuffered isotropic management areas (1 km radius 5314 ha) were performed to compare different management
frequencies: (1) quarter-annual (four operations), (2) semiannual (two operations) and (3) annual (one operation).
The population density range was 0 to 315 targets. A

Leary et al.: Herbicide Ballistic Technology Targeting MiconiaN295

Table 1. Time and costs estimates ($USD) for helicopter operations.
------------------------------OFTa ----------------------------- ----------------------------- Ferryb ---------------------------- ------------------------------ Crewc ----------------------------1/3 ops

2/3 opsFull ops

1/3 ops

2/3 opsFull ops

1/3 ops

2/3 opsFull ops

1 heli 1.7 ($1,667) 3.3 ($3,300) 5.0 ($5,000) 1.1 ($1,133) 1.5 ($1,467) 1.8 ($1,800) 12.0 ($300) 19.5 ($488) 27.0 ($675)
2 heli 3.3 ($3,300) 6.7 ($6,700) 10.0 ($10,000) 2.3 ($2,267) 2.9 ($2,933) 3.6 ($3,600) 20.0 ($500) 32.5 ($813) 45.0 ($1,125)
3 heli 5.0 ($5,000) 10.0 ($10,000) 15.0 ($15,000) 3.4 ($3,400) 4.4 ($4,400) 5.4 ($5,400) 28.0 ($700) 45.5 ($1,138) 63.0 ($1,575)aOperational flight time is the flight time dedicated to surveillance and target acquisition calculated from a fuel cycle of a Hughes
500D performing low-level hovering tactics, estimated at 120 total min minus 20 min round-trip ferry to and from the LZ. A full ops
session accommodates 3 fuel cycles providing 5, 10, or 15 hours of operational flight time for 1, 2, or 3 helicopters, respectively. Utility
helicopter flight services are $1000 hr21.
bFerry time is non-operational flight time for round-trip transport of aircraft from the heliport (0.8 hrs rt) to the LZ and from the
LZ to the management containment area (0.33 hrs rt). Each aircraft is committed to one round-trip heliport ferry and each ops fuelcycle is committed to one round-trip LZ ferry.
cCrew management consists of an operations manager plus two crew members for each aircraft. Logistical responsibilities include
onboard HBT platform assembly, replenishment, refueling, flight following, navigation, surveillance and application. Wage is $25
person-hr21.

mortality factor of 0.542 (the average derived from therepeated flight segments) was imposed on each operation.The undetected targets were calculated from thesubtracted product of the mortality factor, which served
as the target population for the subsequent operations forquarter- and semi-annual strategies, respectively.
A structured matrix model developed for miconia by
Hester et al. (2010) was adopted in this study to simulate
strategies for eradicating incipient miconia populations.
The model estimates annual population growth based on
the probabilities of survival and succession of the (1) seedbank, (2) four distinct juvenile stages and (3) small andlarge mature plants generating positive-feedback by fruit
production augmenting the seedbank. The model was
modified using Meyer (1998) fecundity data where theaverage fruit per panicle was 208 with 195 seeds per fruit.
For this model, a small mature plant only produced two
panicles which is equivalent to 81,120 seed, while a large
mature plant produced 50 panicles with 2,028,000 seed.
The population vector (Xt) of this matrix model started
with a seed bank of 668,075 propagules, 210 juvenile
plants and 2 small mature plants (see Appendix 1). The
average mortality factor of the HBT platform (0.542; see
Table 5) was imposed on the matrix model targeting thejuvenile stages 2 to 4 yr and adult stages, with theassumption that first-yr juveniles were undetectable.
Population densities (mature/juvenile) were selected as
management starting points that included: (1) 2/48, (2)20/74 and (3) 209/1518 representing increasing levels ofinvasion identified along the growth model. The management frequencies were as described above and also included
bi- and triennial strategies.
Expected cost estimations for both models were based ona helicopter flight cost of $1000 USD hr21, HBT
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projectile inventory consumption with a projectile priceof $0.31 USD (Nelson Paint Company, personal communication) and crew costs of $25 USD person-hr21.
Operational flight times were determined by solving forsearch efficiency (min ha21) dependent on plant target
density and the lowest cost determined by the number ofhelicopters needed to accommodate that operation alongwith corresponding ferry times and crew labor (Table 1).
Similarly, projectile inventory consumption was based on
the equation that solves for herbicide dose, which wasestimated to be 25 units per target. The 1-yr population
reduction strategies were reported as basic cost estimatesthat would accommodate a manager submitting an annual
budget request. The matrix model simulation calculated
the net present values (NPV) of projected eradication
timelines at a 6% discount rate applied to the annual costof operations (Hester et al. 2010).
Regression analyses were performed using ordinary leastsquares to determine the effect of plant target density on
empirically derived search efficiency, target acquisition rateand herbicide use (n 5 13) and on expected cost estimates
for the 1-yr population reduction strategies (SPSS. 2009.
PASW Statistics 18, Release Version 18.0.0. SPSS, Inc.,
Chicago, IL).
Results and Discussion

The herbicide efficacy experiment determined HBTTCP200 to be lethal with 5- and 10-unit treatments,
applied either to canopy axial points or the base of theleader stem (Table 2). The HBT-IMZ31 treatments were
not effective. The high velocity projectiles penetrated thethin epidermis of branches with a fraction of the herbicide
creating a ‘‘water soaked’’ mark at the point of impact andTable 2. Miconia survival after treatment with TCP200 and
IMZ31 at the main stem axial points with 5- and 10-unit
applications and basal treatments with 5-unit applications.
Recorded 224 DAT.
ri
Alive
Axial
TCP-5
TCP-10
IMZ-5
IMZ-10

X
X

Basal
TCP-5
IMZ-5

X

rii
Dead

Alive

X
X

riii
Dead

Alive

Dead

X
X
X
X

X

X
X
X
X

X
X

X
X

the remaining portion scattered on to the leaf canopy,
including the undersides. The option to effectively treat
either the base or canopy of miconia is useful in an
operational setting where a clear line of site at the base of
the plant may not be available due to adjacent impeding
vegetation. This herbicide efficacy experiment allowed us toproceed with further evaluating the utility of HBT in ahelicopter platform using the HBT-TCP200 projectiles.
A total of thirteen HBT calibration flight segments wererecorded with a single applicator, three different pilots andsix spotters. Segment time intervals ranged from 13 to
92 min (Table 3). Segment lengths ranged from 508 to

16,276 m with corresponding buffer areas ranging from
4.9 to 121.4 ha. Target acquisitions ranged from 4 to 164
targets per segment and HBT projectile consumption from
2 to 27 pods per segment. Search efficiency, target
acquisition rate and herbicide use were all correlated toplant target density, showing significant positive trends.
Simple linear equations produced best fits for searchefficiency (Figure 2; R25 0.933; P0.05 , 0.001) andherbicide use (Figure 4; R2 5 0.966; P0.05 , 0.001), whiletarget acquisition rate was best fit with a logarithmic
equation (Figure 3; R2 5 0.927; P0.05 , 0.001).
According to the linear search efficiency equation(Figure 2), a helicopter surveillance operation was estimated to search one hectare in 1.13 min (ca. 68 s) where notargets were detected within the buffered area, while theslope coefficient estimated the- complete target acquisition
process to take 0.418 min (ca. 25 s) (Table 4). Thus, inareas with $ 3 targets ha21, the target acquisition timeexceeded surveillance time. According to the logarithmic
equation (Figure 3), the maximum target acquisition rate
was projected to be 143 targets hr21, which was achieved ata density of 164 targets ha21, but exceeded 100 targets
hr21 when the density $ 8 targets ha21. This was
represented in 5 of the 13 calibration flight segments(Figure 3). According to the linear herbicide use equation,
each miconia plant received a mean herbicide dose of 4.79 g
ae triclopyr (0.17 oz) which back calculates to an estimateof 24 projectiles per target. This would suggest an average
plant size with 4 to 5 axial points assuming 100% accuracyof the designated 5-unit application rate. A majority of theTable 3. Recorded HBT calibration flight segment data.
Island/Site

Date

Ta

Lngta

Areab

Targets

Podsc

min
m
ha
--------------------------------------------------------------------------------------------------------------- Maui -------------------------------------------------------------------------------------------------------------Wailua Nui
11/10
61
1,896
7.8
134
27
05/11
69
2,372
8.1
114
19
08/11
64
3,125
15.6
71
15
Waiokamilo 1
04/11
60
1,402
8.2
140
22
08/11
45
1,343
8.7
96
15
08/11
92
3,849
19.8
164
23
Waiokamilo 2
05/11
26
756
6.3
33
5
08/11
13
508
4.9
16
3
08/11
13
571
5.1
19
3
---------------------------------------------------------------------------------------------------------------Kauai -------------------------------------------------------------------------------------------------------------Opaekaa
04/11
39
8,447
58.7
8
3
06/11
73
9,048
70.0
5
2
07/11
48
5,984
51.8
4
2
10/11
69
16,276121.4
72aFlight segment time and length recorded from the start and end points of the track log.
Area calculated from a 50 m buffer on both sides with overlap areas dissolved (see Materials and Methods).
c
Estimated 140 projectiles per pod.
b

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Figure 2. A scatter plot with best fit line (R25 0.927; P, 0.001) with 95% confidence interval (dash lines) of searchefficiency (min ha21) versus target density (targets ha21) for
HBT calibration flight segments (n 5 13) conducted in Wailuanui (black), Waiokamilo 1 (white), Waiokamilo 2 (stripe) andOpaekaa (grey) from November 2010 to October 2011. See
Table 4 for regression coefficients.

Figure 4. A scatter plot with best fit line (R2 5 0.966; P, 0.001) with 95% confidence interval (dash lines) of herbicideacid equivalent amount (grams ae ha21) versus target density(targets ha21) for experimental HBT helicopter operations (n 513) conducted in Wailua nui (black), Waiokamilo 1 (white),
Waiokamilo 2 (stripe) and Opaekaa (grey) from November 2010
to October 2011. See Table 4 for regression coefficients.

targets had 3 to 4 axial points and the accuracy of theapplication was not measured during the calibrations, but it
was less than 100%. Furthermore, an axial point may havereceived . 5 units, but not more than 10 units. In
comparison to other registered triclopyr products, thehighest use rate of HBT-TCP200 was 1.09% of the
maximum allowable rate of 8.96 kg ae ha21(8 lbs ae acre-1)
while the remaining twelve calibration flight segments had
calculated use rates that were , 1%. As described below,
these low use rates resulted in . 94% treatment efficacy.
These calibrations highlight the efficiency of a surveillance
operation that combines effective target control, which isfundamental to an effective containment strategy andfurther contributes to a limited knowledge base relating
control effort to weed density (Buddenhagen and Yañez
2005; Cacho et al. 2007, Campbell et al 1996; Hester
2010; Panetta 2009; Panetta and Lawes 2005).

Previously undetected targets were identified and treatedin subsequent overlapping operations. The range of
detection efficacy calculated among the sites was 0.427
to 0.708 with a mean of 0.560 (Table 5). Operational
treatment efficacy was determined in repeat segments byidentifying survivors of a previous application. Typicalsymptoms included severe defoliation and necrosis associated with the herbicide treatment, but with intact lateralbranches retaining photosynthetic leaf canopy. Thus,
survivorship was not likely due to a malfunction of the
HBT-TCP200 projectiles, but rather a condition of theapplication under a simulated operational setting. Regardless, the lowest operational treatment efficacy recorded was
0.941 at Opaekaa with a mean of 0.972 for all of thesegments. Mortality factors (i.e. product of detection andtreatment efficacies) among the segments had a range of
0.424 to 0.667 with a mean value of 0.542 (Table 5).
These calibrations suggest that detection efficacy is a more
influential correlate of mortality factor, highlighting thedifficulty of plant detection in these natural environments,
but also validates the consistency of this herbicide
application platform (e.g. 5-unit dose).
This study recognizes mortality factor (Cacho et al.
2006) as an important parameter generated from these
HBT calibrations. A mean of 0.542 would suggest a needto improve miconia detection through better surveillancetechniques. Panetta and Cacho (2012) suggest that a
structured search effort with uniform coverage and overlap
should optimize target detectability. According to Cachoet al. (2007) coverage is a product of speed, time anddetectable sight distance. This study utilized three different
pilots and six different spotters for conducting thecalibration flight segments (n 5 13). All participants had
several years of experience in helicopter surveillance
operations and miconia detection. The speeds observed

Figure 3. A scatter plot with best fit line (R2 5 0.924; P, 0.001) with 95% confidence interval (dash lines) of target
acquisition rate (targets hr21) versus target density (targets ha21)
for experimental HBT helicopter operations (n 5 13) conductedin Wailua nui (black), Waiokamilo 1 (white), Waiokamilo 2(stripe) and Opaekaa (grey) from November 2010 to October
2011. See Table 4 for regression coefficients.

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Table 4. Regression coefficients as performance analytics for search efficiency, target acquisition rate and herbicide dose from empiricalcalibrations (n 5 13) and cost components for simulated 1-yr extirpation strategies of different management frequencies, all relative totarget density (T ha21).
------------------------------Coefficients ---------------------------mb

Dependent variable
Empiricala
Search efficiency (min ha21)
Target acquisition rate (targets hr21)
Herbicide dose (g ae t21)
Simulationb
Qrt; MF 0.96 ($USD)
Semi; MF 0.79 ($USD)
Annu; MF 0.54 ($USD)
a
b

R2

P

0.418321.533*ln
4.79371.130757.885
0

0.933
0.927
0.966

, 0.001, 0.001, 0.001

23.81
20.39
13.40

39,111
19,468
9,811

0.996
0.994
0.987

, 0.001, 0.001, 0.001

Refer to Figures 2, 3 and 4 for search efficiency, target acquisition rate and herbicide dose, respectively.
Refer to Figure 5 for simulations.

for these flight segments could be described as a slow hover
within a ‘‘comfort’’ zone for efficient target detection,
which was estimated at 5.3 km hr21 (see y-intercept forsearch efficiency in Table 4). Speed reduction might
improve target detection but with an added expense andthe possibility of increasing pilot fatigue.
Miconia detectability is impeded by heavy vegetationand extreme topography, which are typical of tropical wet
forest ecosystems. Plant size was also a factor in
detectability. A majority of the acquired plant targets wereat least 1 m tall, indicating a minimum age of 2 yr, while amajority of the incipient populations may consist ofundetectable 1-yr juveniles. This highlights two points: (1)miconia detection is likely to be less than 100% and (2)recruitment of new detectable miconia can be expected inmanagement areas within 1 yr following initial population
reduction. These two conditions warrant a commitment tofrequent, repeated surveillance operations of a management
area that extends beyond reaching an undetectable level, if
the ultimate goal is to actually achieve complete eradicationof the incipient population. Ideally, this would occur undera policy that minimizes expected costs based on knowledgeof the target species’ biology and performance of theoperational strategy (Burnett et al. 2007).
Operational costs were projected for simulated 1-yr
population reduction strategies with different surveillancefrequencies and plant target densities (Figure 5; Table 4).
Costs for all strategies exhibited significant positive linear
trends to plant target density (Table 4; R25 0.987–0.996,
P0.05 , 0.001) with semi- and quarter-annual strategies
costing two- and four-fold higher than the annual strategy,
respectively, where no targets were present. However,treatment costs (i.e. slope) progressively increased fromlowest to highest frequency. With the cost of the herbicide

Table 5. Empirical Estimates for Detection Efficacya (DE) and Operational Treatment Efficacyb (OTE) to calculate Mortality Factors(MF) from overlapping areas with repeated calibrations.
Wailua Nui (7.8 ha)
Segments
Targets
Survivors
DE
OTE
MF

1
134
—
—
—
—

2
110
4
0.549
0.970
0.533

3
65
5
0.629
0.955
0.600

Waiokamilo 1 (7.3 ha)
1
140
—
—
—
—

c

2–3
188
1
0.427
0.993
0.424

Waiokamilo 2 (5.7 ha)
1
33
—
—
—
—

c

2–3
35
0
0.485
1.000
0.485

Opaekaa (121.4 ha)
1–3c
17
—
—
—
—

4
7
1
0.708
0.941
0.667

a

DE is calculated as the ratio of the previous targets from the total combined targets with the subsequent operation and it is assumed
that all new targets in the subsequent operation were previously undetected and not new recruits.
b
OTE is the ratio of effectively treated targets from the total targets, which is derived from the number of confirmed survivors
identified in the subsequent operation.
c
Combined calibrations overlapping the entirety of the of the previous/subsequent calibration and were conducted within 1 week ofeach other with targets and survivors reported as a composite value.
Leary et al.: Herbicide Ballistic Technology Targeting MiconiaN299

Figure 5. Expected operational cost projections of simulated
1-yr extirpation strategies within a 314-ha buffer management
area with incipient population densities up to 1 target ha21. Each
operation is assigned an MF 5 0.542 with different management
frequencies: Qrt (4 ops; MF 5 0.96), Semi (2 ops, 0.79) andAnnu (1 operation; MF 5 0.54). Calculations based on singlehelicopter operations. The solid line represents a semi-annual
helicopter surveillance strategy with two operations where notargets are detected to confirm extirpation. See Table 4 forregression coefficients.

dose remaining static at $7.75 per plant, the cost increases
corresponded to the extra flight time for overlapping
coverage of the same area, regardless of whether the target
was undetected in a prior operation or with treatment
confirmation in the subsequent operation. The increases in
population reduction potential (i.e. mortality factor) forthe more frequent strategies is less than the corresponding
cost increases, which reflects the difficulties of treating thelast remaining targets to achieve undetectable levels andcorroborates with Burnett et al. (2007) suggestion to defer
management at extremely low target densities. The cost to
search a 314-ha management area with no targets detected,
along with an added surveillance operation to confirm notargets was estimated to be $19,657 USD, and served as areference to opportunity cost for the other management
options (Figure 5). For instance, this cost is comparable toa single surveillance operation of the same size managementarea, but with the opportunity to treat up to 734 targets at
a mortality factor of 0.54, while conversely the higher
frequency strategies lose opportunities to confirm undetectable levels in other management areas.
The matrix model simulated these same strategies, andincluded bi- and triennial schedules over a multi-yr period
until complete eradication was achieved by exhaustingpredetermined seed banks, (Table 6). For all simulations,
NPVs decreased proportionally to operational frequency
and were largely influenced by the total number ofoperations and the discount rate applied each year acrossthe timeline. The quarter-annual strategy achieved eradication with the shortest timelines, but also with the highest
300

N

Invasive Plant Science and Management 6, April–June 2013

number of operations and at the least discounted rates,
thus, resulting in the highest NPVs. The triennial strategy
eradicated the smallest population with the lowest NPV,
resulting from the longest timeline with the most
discounted rates. However, this strategy failed to eradicate
the two larger vector populations with reduction being
outpaced by recruitment. The biennial strategy eradicatedthese larger vector populations, with the longest timelines
and most discounted rates resulting again in the lowest
NPVs. This illustrates the value of maximizing discounted
rates with long-term extensions to strategies. However, this
could only be accounted for with a reliable commitment tosustained resources and if those resources were actuallyinvested on years where management was not scheduled.
Miconia management programs in Hawaii operate underno such mandate and experience fiscal fluctuations withannual renewals.
These short- and long-term projections (Figure 5;
Tables 4 and 6) are deterministic by producing expected
outcomes, which can vary from actual results, but should
continue to improve with updates in quantitative ecology
and operations research (Hester et al. 2010). Cost estimatesand NPVs reported in this study are within range ofreported projections from Australia (Hester et al. 2010).
These expected cost and NPV projections assume complete
surveillance of a 314-ha isotropic buffer, but is likely to be
an impractical management unit in heterogeneous environments (Murphy et al. 2008). Spatial analyses of
population distribution and suitable habitat will become
valuable contributions in management area prioritization
and resource allocation. For example, ravines and gullies
are known to serve as conduits in frugivorous dispersal andgravitational migration of propagules (Metcalf et al. 1998;
Murphy et al. 2008). New information from Tahiti has
identified several parameters, including topgraphic slope
and aspect, as identifiers of suitable habitat for miconia(Pouteau et al 2011). The projections from this study arelikely to over-estimate resource requirements to accomplish
population reduction goals, although the performance ofthe HBT platform should be consistent regardless ofmanagement area designation. Future operational use
patterns of the platform are expected to improve thecalibrations with larger data sets generated by multiple
applicators and a broader range of scenarios. The protocols
adopted in this study for recording basic operationalparameters and calibrating performance should be universal
to most weed management techniques in natural areas
where search effort and treatment efficacy are both criticalfeatures to successful operations (Cacho et al 2007). The
HBT platform is presented as a complement to existing
ground and aerial efforts for miconia management in
Hawaii. Accurate calibrations of these conventional
techniques will further support decisions for futureassignments where HBT might be best suited.

Table 6. Projected long-term management strategies to eradicate incipient miconia populations within a 314 ha isotropic buffer
management area with an operational mortality factor (MF) 5 0.542.
Xta (adult/jv)
2/48

20/74

209/1518

Scheduleb

Years/opsc

Adult/jvd

Mean MFe

NPVf ($10003)

Qrt
Semi
Annu
Bi
Tri
Qrt
Semi
Annu
Bi
Tri
Qrt
Semi
Annu
Bi
Tri

13/38
13/23
13/13
19/10
58/20
15/46
15/27
16/16
29/15
—
21/69
21/38
25/25
63/32
—

2/264
2/277
3/329
17/455
123/1,736
20/54324/62834/856110/1,653—
218/8,887
281/10,111
550/13,587
1,491/23,050
—

0.977
0.819
0.565
0.325
0.225
0.971
0.809
0.556
0.306
—
0.961
0.782
0.542
0.405
—

272.87158.90
87.46
58.48
57.17
317.12180.22102.6972.99—
526.56319.58213.49164.79—aInitial vector population of adults and detectable juveniles (yr 2 to 4).
Operation frequency: Qrt - four operations yr21; Semi- two operations yr21; Annu- one operation yr21; Bi- one operation two
21
yrs ; Tri- one operation three yrs21.
c
Total yr and operations projected to achieve incipient population extirpation.
d
Total adults and juvenile (yr 2 to 4) targets acquired to achieve incipient population extirpation.
e
Mean annual mortality factor based on an operational mortality factor of 0.542 compounded by the number of operations.
f
Net present value investment ($USD) based on cost of helicopter operations (see Table 2), projectile inventory consumption andannual discount rate of 6%.
b

A comprehensive miconia management strategy islimited by available fiscal resources, which force decisions
to be made between risk aversion and budget optimization(Burnett et al. 2007; Hester et al. 2010). An optimal policy
for miconia management minimizes the present values ofmanagement costs and residual damages along an infinite
timeline, that would even dictate management deferment
for low-density populations, where the marginal cost to
search and treat these remaining individuals is extremely
high (Burnett et al. 2007). Murphy et al. (2008)
recommended the establishment of management units
with a minimum 1000 m radial buffer, but in the same
report identified 95% of the targets treated within a 500 m
buffer. According to Burnett et al. (2007) and in this study(see Figure 5) elimination of that last 5% becomes
exceedingly more difficult and costly. This study suggests
a triennial schedule as an optimum strategy for the smallest
incipient population, although it must accommodate a 58yr timeline with an 8-fold recruitment of the mature
population. Anecdotally, we have encountered multiple
occasions confirming the establishment of mature stands
when reentry to a site exceeds 2 yr. From a practitioner’s
standpoint, a budget optimization approach is likely to
be viewed as too risky, particularly when funding pro-visions fluctuate annually with no permanent mandate ofsupport.
For invasive weed management, marginal costs can beinterpreted different ways, with incremental units based ontarget numbers or net treated area (Buddenhagen andYañez 2005; Campbell et al. 1996; Rejmánek and Pitcairn2002). Resources dedicated to control inputs may be
negligible compared to resources dedicated to search effort(Hester et al. 2010). Helicopter flight time was a dominant
cost component for analyzing HBT platform performance.
We identified surveillance operations confirming undetectable levels (i.e. no targets detected) to have the lowest
marginal cost that could be applied to a management area.
Delimiting incipient populations is critical to effective
containment of miconia, and should include expanding
surveys into unknown areas despite the probability of notdetecting new populations (Brooks et al. 2009; Cacho et al.
2010) However, the strategy must acknowledge theconundrum of an opportunity lost in reducing (i.e. target
treatment) known, incipient populations.
This study does not attempt to provide concretedecisions in favor of extreme risk aversion or expected cost
minimization. However, miconia is an autogamous species
with rapid maturity, high fecundity and a large dispersal

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301

range making a single plant in a remote area a high value
target that can only be detected with resources dedicated tofrequent, overlapping surveillance operations. The best
utility identified so far for the HBT platform is throughintegration into aerial surveillance operations where
nominal herbicide use rates translate into significant flighttime cost savings and provides streamlined efforts towards
effective miconia containment.
Acknowledgments

Funding for this project was provided in part by the Maui
County Office of Economic Development Special Grants
Program, Hawaii Invasive Species Council Technology Grants
Program, USDA-CSREES Tropical Subtropical Agriculture
Research Program, USDA-NIFA Rural Resources Extension
Act, and the USDA- NRCS Conservation Innovation Grant.
We thank Nelson Paint Company, Dow Agrosciences LLC.,
BASF Corp. and The Wilbur Ellis Company for their current
and past collaborations. We thank Keren Gundersen, Lloyd
Loope, Chuck Chimera and two anonymous reviewers for
improving this manuscript with thoughtful suggestions.
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Received April 2, 2012, and and accepted January 7, 2013.

Appendix 1. Stage matrix (H) and vector populations (Xt) adopted from Hester et al 2010.
H5

a0
Pfruit
0
0
0
0
0
0

0
Psb
G
0
0
0
0
0

0
0
0
Pjv1
0
0
0
0

0
0
0
0
Pjv2
0
0
0

0
0
0
0
0
Pjv3
0
0

0
0
0
0
0
P6
Pjv4
0

Fsa
0
0
0
0
0
P7
Psa

Fla
0
0
0
0
0
0
Pla

Xt 5

SBa
jv1
Jv2
Jv3
Jv4
sa
la

2/48
20.80
3,418
37
8
3
0
2

20/74
47.99
4,872
44
11
19
8
12

209/1518
675.4595,440
1012
257
249
83
126

Seed bank values reported in 3 106.

Leary et al.: Herbicide Ballistic Technology Targeting Miconia

N

303