MARINE MAMMAL SCIENCE, 26(2): 296–308 (April 2010)
2009 by the Society for Marine Mammalogy
A simple laser photogrammetry technique for measuring
Hector’s dolphins (Cephalorhynchus hectori) in the ﬁeld
Department of Marine Science,
Department of Zoology
University of Otago,
P. O. Box 56, Dunedin, New Zealand
STEVE DAWS ON
Department of Marine Science,
University of Otago,
P. O. Box 56, Dunedin, New Zealand
Department of Zoology,
University of Otago,
P. O. Box 56, Dunedin, New Zealand
The ability to measure and age individuals within a population has many impor-
tant applications, for example, for examining growth and determining size class.
We developed a simple photogrammetric system using two parallel lasers and a
digital camera, in order to measure dorsal ﬁn dimensions of free-ranging Hector’s
dolphins. Laser dots were projected onto the ﬁn, providing scale, thus allowing
measurement as well as simultaneous photo-ID of 34 individuals from ﬁn nicks
and other marks. Multiple measurements (≥5) were available for six individuals;
these resulted in mean CVs of 3.71% for ﬁn length and 3.76% for ﬁn height. Errors
due to variations in angle and measurement were quantiﬁed via photography of
a ﬁberglass Hector’s dolphin model. Allometric measurements and age data were
collated from 233 autopsied Hector’s dolphins. Using these data, ﬁn length was
found to be a better predictor of total length (females r2=0.732, males r2=0.678)
than ﬁn height. Gompertz age/length growth curves were ﬁtted to these individ-
uals. Linear regressions were used to estimate total length for 34 individuals from
laser-metrically estimated ﬁn base length. Individuals were then assigned one of
three age categories. This system shows promise as a noninvasive way of measuring
individuals, while allowing simultaneous photographic identiﬁcation.
Key words: photogrammetry, Hector’s dolphin, Cephalorhynchus hectori, length, age
WEBSTER ET AL.: PHOTOGRAMMETRY 297
The ability to age and measure individuals within a population is useful for a
variety of reasons. Length estimation is important for examining growth (Clark et al.
2000), determining size class (Cubbage and Calambokidis 1987), subspeciﬁc status
(Baker et al. 2002), different geographic forms (Perryman and Lynn 1993, Perryman
and Westlake 1998, Jaquet 2006) and the extent of sexual size dimorphism (Ramos
et al. 2002, Martin and Da Silva 2006). Age estimates are required for age-structured
population models (Slooten and Lad 1991, Cameron et al. 1999). Age and size also
determine maturity and inﬂuence reproductive success (Martin and Rothery 1993).
It is difﬁcult to calculate exact ages for marine mammals; however, a number of
techniques are commonly used to provide an estimate of age. The standard procedure
for estimating age in odontocetes and pinnipeds involves counting the incremental
growth layers in tooth sections (Perrin and Myrick 1980, Myrick et al. 1984). This
technique has been used on live animals but is highly invasive as it involves capture
of the animal and extraction of a tooth (Arnbom et al. 1992, Childerhouse et al. 2004,
Bell et al. 2005). Long-term photo-ID studies can also provide age data (Hamilton
et al. 1998), but this requires intensive ﬁeldwork over the study species’ lifetime
and typically obtains a minimum age, unless the individual is marked as a calf (e.g.,
Kraus et al. 1986).
Photogrammetry is a well-established, noninvasive method for measuring individ-
uals, both in terrestrial and marine environments (e.g., elephants, Loxondonta africana,
Schrader et al. 2006; gorillas, Gorilla gorilla, Breuer et al. 2006; and northern blueﬁn
tuna, Thunnus thynnus thynnus, Costa et al. 2006). Photogrammetric techniques are
particularly useful as noninvasive ﬁeld methods for marine mammals, as they do not
require capture. There are two general approaches to photogrammetry, either stereo-
photography or single camera photography. Stereo-photogrammetry uses a pair of
overlapping images to create a 3-D optical model, in which scale is provided by the
known distance between the cameras and the lens magniﬁcation (e.g., Ratnaswamy
and Winn 1993, Dawson et al. 1995, Br¨
ager and Chong 1999, Waite et al. 2007).
Single camera photogrammetry requires either a known object in the image for scale
(e.g., Best and R¨
uther 1992, Flamm et al. 2000) or a measurement of the range to
the individual (e.g., Gordon 1991, Spitz et al. 2000, Jaquet 2006). A more recent
development in single camera photogrammetry uses a pair of parallel lasers to provide
scale in the images (Durban and Parsons 2006, Rowe and Dawson 2009).
A previous stereo-photogrammetric system was developed for Hector’s dolphins
to measure bowriding dolphins (Br¨
ager et al. 1999). While stereo-photogrammetry
is inherently more accurate than single camera systems, and 3-D measurements are
possible, this type of system was cumbersome both in the ﬁeld and during analysis.
Also, their greater accuracy may be of little advantage when measuring animals that
are ﬂexible (Dawson et al. 1995).
Laser photogrammetry is a simple, single camera method that has previously
been used to measure rockﬁsh (Sebastes sp., Gingras et al. 1998, Yoklavich et al.
2000), to quantify and measure ﬁsh assemblages around oil platforms (Love et al.
2000), to measure a variety of ﬁsh species in the Bay of Biscay (Rochet et al. 2006)
and to measure dorsal ﬁn dimensions of orca (Durban and Parsons 2006). This
method uses two parallel lasers mounted on a digital camera. The lasers project
dots at a known distance apart in the photographic images, to establish scale and
allow measurement of the dorsal ﬁn. Further, the same images can be used in standard
photo-ID, thus identifying and measuring individuals simultaneously. Growth curves
and regressions constructed from dissection data can then be used to relate the dorsal
ﬁn dimensions to total length and age for Hector’s dolphins.
298 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Combined photo-ID and laser photogrammetric photographs were taken during
boat surveys off the coast of Banks Peninsula, New Zealand, between December 2005
and February 2008. Photographs were taken from a 6 m, outboard powered research
vessel. A Nikon D1H digital camera (Nikon Imaging Inc., Tokyo, Japan) with an
80–200 mm f2.8 zoom lens was used with two laser pointers set in a high-density
nylon block secured to the tripod mount. The block mount was custom-made to ﬁt
the laser pointers, which were set at 10 cm apart and were adjustable for calibration.
The lasers (Z-bolt model BTG-10, wavelength 532 nm, output power <5mW)
were eye safe, although direct eye contact should be avoided.
Each day before use, the lasers were tested at two different distances (2.3 m and
6.5 m) to check that they were parallel. These distances were chosen as they are within
the typical range for Hector’s dolphin identiﬁcation photographs. In the ﬁeld, photos
were taken of the dorsal ﬁn of any identiﬁable dolphins so that the laser dots were
projected onto the ﬁn or body (Fig. 1).
Each photograph was graded for quality to ensure that it had been taken from as
close to side-on to the dolphin as possible, with laser dots clearly visible, with dorsal
ﬁn in focus and taken from approximately within the calibration range.
Dorsal ﬁn height and dorsal ﬁn base length were measured from the digital images
using graphics software Intaglio v.2.9.3. The known separation distance of the lasers
(10 cm) was used to calibrate the photographs. Measurement tools within the software
were used to measure dorsal ﬁn dimensions. Measurements of dorsal ﬁn base length
were taken from the midpoint of the curve at the anterior edge of the ﬁn to the notch
at the posterior edge of the ﬁn along the base of the ﬁn (Fig. 1). Measurements of
dorsal ﬁn height were taken by drawing a line parallel to the base of dorsal ﬁn, which
just touches the top of the ﬁn, then extending a line perpendicular to the two parallel
lines (Fig. 1).
Figure 1. Digital photograph of a Hector’s dolphin dorsal ﬁn with projected laser dots and
dorsal ﬁn measurements.
WEBSTER ET AL.: PHOTOGRAMMETRY 299
Sources of Error
Several sources of error are present at all stages of this photogrammetric method,
both in the ﬁeld and during the measurement process. Errors in the ﬁeld include
those which occur during the photographing of individuals, due to the alignment of
the lasers and those occurring naturally due to the ﬂexing of individuals. Horizontal
axis error, which occurs when the dolphin does not surface exactly side-on to the
camera, and parallax error, which occurs when the photographer is looking down on
the subject (Durban and Parsons 2006), both cause negative biases in measurements.
Flexing of the dolphin’s body may subtly change the shape and dimensions of
the dorsal ﬁn. Additionally, sensitivity of the nylon laser mount to temperature
ﬂuctuations may lead to alignment errors. In the ﬁeld these errors were minimized
by using the same photographer (TW), taking care that photographs were taken
as close to perpendicular as possible, from ranges of approximately 2–6 m, and by
calibrating the lasers daily. In analysis we discarded any images that were not sharp,
poorly exposed, taken from too far away, or which appeared to be nonparallel.
Errors in the measurement process arise from three major sources: variability
between observers, variability in measurement method and poorly deﬁned metrics
(or deﬁnition error). These were minimized by having the same person take all of the
measurements, following a standardized set-up procedure.
It was not possible to estimate directly the magnitude of all errors involved in
this photogrammetric method, as Hector’s dolphins of known size are not available
for comparison in the ﬁeld. Instead, error reduction strategies were employed and
indirect techniques were also used to quantify errors where feasible.
The combination of errors (except ﬂexing) was measured by taking three replicate
photographs of a ﬁberglass Hector’s dolphin model at each of 5◦increments between
0◦and 55◦from perpendicular to the model and at three different distances (2.5,
5, and 7.5 m). This was done because while some errors (e.g., horizontal axis error,
parallax error) should be strictly trigonometric, other errors (e.g., deﬁnition error,
alignment of lasers) may not be. Replicate measurements on the same photograph
were not carried out in succession.
The precision of measurements taken from Hector’s dolphins was quantiﬁed by
measuring randomly chosen photographs of those individuals photographed multiple
times. Here too, measurements were not carried out in succession. A model II analysis
of variance (ANOVA) was used to partition the variance of dorsal ﬁn measurements
into “within” and “among” dolphins, and then calculate percentage measurement
error. Measurement error is deﬁned here as the variability of repeated measurements
of dorsal ﬁn dimensions taken on the same individual, relative to the variability of
these dimensions among individuals (see Bailey and Byrnes 1990 for method),
%ME =100 s2
Measurement data from bycaught and stranded Hector’s dolphins were collated
from a number of different sources (Slooten 1991; Duignan et al. 2003, 2004;
Duignan and Jones 2005). Measurements gained during autopsies by experienced
researchers, and age estimates from counting GLGs in teeth (e.g., Slooten 1991),
300 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
are assumed to be without error. A linear regression was ﬁtted to dorsal ﬁn height
and dorsal ﬁn length against total length. Von Bertalanffy (Von Bertalanffy 1938),
Gompertz (Gompertz 1825) and Richards (Richards 1959) growth curves were used
to describe growth. Growth functions of the following form were ﬁtted using least
squares estimation of the parameters in program JMP v5
Von Bertalanffy: Lt=L∞(1 −bexp(−kt))
Richards: Lt=L∞(1 −bexp(−kt))M
where L∞is asymptotic total length (or ﬁn height or ﬁn length), tis age in years, k
is a growth rate constant, bis the constant of integration, and Mspeciﬁes the relative
position of the asymptote.
Multiple photographs of a Hector’s dolphin model examined a combination of
errors and showed that deviations of up to 20◦from perpendicular resulted in dorsal
ﬁn measurements within 2% of actual values. Over this range of angles, there were
no obvious biases caused by variation in range (Fig. 2).
The model II ANOVA using data from dolphins that had been repeatedly pho-
tographed and measured showed that the variation between individuals was far
greater than the variation between multiple remeasurements of the same photo-
graph. The results of the ANOVA were highly signiﬁcant for dorsal ﬁn height
(F=2,320.04, df =32, 132, P<0.001) and dorsal ﬁn length (F=2,216.87,
df =325, 132, P<0.001). Percentage measurement error (see formula in Meth-
ods) was also minimal at 0.22% for dorsal ﬁn height and 0.23% for dorsal ﬁn
Ninety-ﬁve images of 34 identiﬁable dolphins showed projected laser dots, were
sharply focused and showed ideal orientation of the individual to the camera. Twenty
Figure 2. Mean error in dorsal ﬁn length measurements with angle from perpendicular.
WEBSTER ET AL.: PHOTOGRAMMETRY 301
Figure 3. Variability in dorsal ﬁn base length measurements for six individuals pho-
tographed ﬁve or more times. Minimum age and sex are given under the identifying number
of each individual.
individuals were of known sex (12 females and 8 males). The number of photographs
for each individual ranged from 1 to 19 (¯x =2.88). Dorsal ﬁn height ranged from
8.04 cm to 11.57 cm and ﬁn base length was in the range from 17.10 cm to
Six identiﬁable individuals of known sex and known minimum age (calculated
using photo-ID data) were photographed ﬁve or more times (including two individ-
uals on different days, Fig. 3). These individuals show an increase in dorsal ﬁn length
with age, as expected. The mean CV of dorsal ﬁn base length for these individu-
als was 3.71% (range 1.57%–5.71%) and for dorsal ﬁn height was 3.76% (range
Allometric Measurements and Growth Curves
A total of 233 individuals with either two or more relevant allometric measure-
ments, or estimated age (from GLGs) and one or more measurements were repre-
sented in the autopsy data. Ninety four percent of these dolphins were of known sex
(127 males and 92 females) and 73.4% were of known age.
302 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Figure 4. Gompertz growth curves for male and female Hector’s dolphins.
Von Bertalanffy, Gompertz, and Richard’s growth models were ﬁtted to autopsy
data for total length, dorsal ﬁn height, and dorsal ﬁn base length for male and
female Hector’s dolphins separately. The Richard’s growth model, typically, did not
converge, and was therefore considered unreliable for these data. There was very little
difference between Von Bertalanffy and Gompertz growth functions. Von Bertalanffy
growth curves were a marginally better ﬁt and had a slightly lower residual of the sum
of squares. However, Gompertz growth curves ﬁtted the lower end of the data (i.e.,
the younger animals) much better than Von Bertalanffy curves. Since this portion of
the curve is most important for growth, Gompertz curves were chosen (Fig. 4).
Linear regressions showed that dorsal ﬁn base length was a far better predictor
of total length (females r2=0.73, males r2=0.69; Fig. 5) than dorsal ﬁn height
(females r2=0.51, males r2=0.58; Fig. 6). Females had a slightly better relationship
between ﬁn base length and total length than males (Fig. 5).
WEBSTER ET AL.: PHOTOGRAMMETRY 303
Figure 5. Relationship between total length and dorsal ﬁn base length for male and female
Hector’s dolphins. The regression relationship labeled “Unknown sex” is for all data including
three individuals of unknown sex.
The regressions were used to estimate total length from data on dorsal ﬁn base
length for 34 individuals that were measured using the photogrammetric method.
Gender speciﬁc linear regressions were used where possible. The estimated total
lengths for females ranged from 115.8 cm to 143.1 cm. Males were slightly smaller
between 97.1 cm and 126.0 cm. Individuals of undetermined sex had total lengths
of between 110.9 cm and 137.1 cm.
It has not been possible to estimate age from photogrammetric measurements,
for two reasons. Firstly, there is a great deal of variability in the body measurement
data; for example, 2-yr-old males range from 90 to 120 cm. Also, the nature of these
growth curves is that they plateau at approximately 5–6 yr. Thus a female ≥134
cm could be anywhere between 6 and 20 yr old. It was possible, however, to place
laser-metrically measured individuals into broad age categories, based on their dorsal
ﬁn base length (Table 1). Age categories were determined using information on ﬁn
length measurements, estimated age (from tooth sections) and maturity status from
the collated autopsy data.
Individuals that are either particularly large for their age or particularly small are
difﬁcult to age. An intermediate category (Table 1) encompasses these individuals
as well as those of medium ﬁn length that are unable to be assigned to either the
juvenile or mature category.
304 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
Figure 6. Relationship between total length and dorsal ﬁn height for male and female
Hector’s dolphins. The regression relationship labeled “Unknown sex” is for all data including
ten individuals of unknown sex.
The laser photogrammetric technique applied here was ﬁrst tested on cetaceans
by Durban and Parsons (2006) to measure the dorsal ﬁn height of orca, and has
since been used on bottlenose dolphins (Rowe and Dawson 2009). These systems are
inexpensive, require very little equipment, and are easy to set up and use. Another
major beneﬁt is that identiﬁcation photographs are obtained simultaneously.
This method resulted in a mean CV of 3.71% for dorsal ﬁn base length and 3.76%
for ﬁn height, which compare favorably with other photogrammetric techniques for
Tabl e 1 . Age categories determined by dorsal ﬁn length for individuals of either known or
unknown sex, and the number of individuals in each category (n).
Male Female Unknown gender
Juvenile ≤18.2 cm ≤19.2 cm ≤18.2 cm
Intermediate 18.3–20.5 cm 19.3–21.5 cm 18.3–21.5 cm
Mature ≥20.6 cm ≥21.6 cm ≥21.6 cm
WEBSTER ET AL.: PHOTOGRAMMETRY 305
measuring cetaceans in the ﬁeld. Stereo-photogrammetric measurement of blowhole
to dorsal ﬁn distance in sperm whales using a boat based technique yielded a mean
CV of 4.38% (Dawson et al. 1995). An underwater videogrammetry method for
obtaining lengths of humpback whales resulted in a mean CV of 3.08% for mothers
and 2.57% for escorts (Spitz et al. 2000). Median CVs varied from 1.29% to 4.56%
for various morphometric measurements of right whales (Best and R¨
uther 1992). A
median CV of 1.3% was obtained for individual ﬂuke measurements of sperm whales
Errors will never be completely eliminated from this photogrammetric system but
they can be quantiﬁed and reduced where possible. Accuracy was demonstrated by
photographing a life-size Hector’s dolphin model of known dimensions. When the
model was 20◦from perpendicular to the camera, theoretically, parallax error alone
would produce an error of 6%. However, a combination of errors are acting, some
of which apparently counteract the parallax error, so that all measurements from the
laser photogrammetric system were within 2% of the actual measurements. Similarly,
a measurement technique applied to sperm whale ﬂukes (Jaquet 2006) found that
errors were small when the angle between the ﬂuke surface and a plane perpendicular
to the camera was <10◦and that at angles >20◦measurements do not provide
reliable size estimates. Measurement errors (quantiﬁed via multiple, nonsequential,
remeasurement of the same images) were low for this photogrammetric method
(0.22–0.23%). Also, it should be remembered that because dolphins are inherently
ﬂexible, even a perfect system used repeatedly on the same individual would not
produce exactly the same measurements.
Dorsal ﬁn base length was found to be a better predictor of total length than dorsal
ﬁn height and hence was used to estimate length of living dolphins. Individual
lengths calculated for these animals were within the known total length range for
Hector’s dolphins (Slooten 1991; Duignan et al. 2003, 2004; Duignan and Jones
Due to variation in body measurement data, age could not be predicted accurately
from measurements of dorsal ﬁn dimensions and growth curves. Broad age categories
can, however, be assigned to individuals measured using the laser photogrammetric
technique. This method therefore shows promise to provide ﬁeld data that might be
used, for example, in a stage-structured population model. This would avoid the need
to use potentially biased age distributions gained from dead animals, the majority
of which have been incidentally killed in gill nets (e.g., Slooten 1991).
We noted that the black mounting block sometimes became warm in the sun,
and this may have affected laser alignment. Using white nylon material (instead of
black) is advised. Also, we noted that the Z-bolt laser pointers that we used were not
collimated, that is, the axis of the laser beam and the laser pointer’s tubular body
were not the same. We corrected for this during calibration, but in future would use
higher quality lasers, in which this is adjustable.
The laser photogrammetric method trialed here has several potential future uses
for marine mammals. The system is particularly useful for those species that are
identiﬁable from nicks in the dorsal ﬁn. Measurement of body proportions could
potentially be applied to individuals to help determine health status and pregnancy in
the ﬁeld (e.g., Pettis et al. 2004). Age estimation using this technique and age-length
data would be more effective in species that mature late and grow for much of their
lives. Growth curves need to be examined beforehand and the relationship between
a particular measurement and age needs to be tight for age determination to be
effective. In order to establish growth curves with sufﬁcient data points, a signiﬁcant
306 MARINE MAMMAL SCIENCE, VOL. 26, NO. 2, 2010
number of dead animals would need to be available for measurement. This may limit
studies, for example, to species which mass strand or those with signiﬁcant bycatch.
Differences in length between subspecies could be detectable using this laser-metric
technique, assuming that the difference in length is greater than the errors involved
(e.g., common dolphins, Perryman and Lynn 1993; spinner dolphins, Perryman and
Westlake 1998). The use of scale in identiﬁcation photographs may elucidate the
causes of identifying marks, for example, the examination of puncture wounds to
identify predator species or scars from collisions with propellers in order to identify
the type of vessel involved. Last, measurement data might be a useful adjunct in
photo-ID, allowing discrimination of different sized individuals that bear similar
This study was possible thanks to support and funding from the New Zealand Whale
and Dolphin Trust. Thanks to Will Rayment for his assistance with data collection and
Black Cat Group for logistical support. Many thanks to the Fraser family for their help
and support at Banks Peninsula. The University of Otago Research Committee provided a
University of Otago Postgraduate Publishing Bursary enabling the completion of this article.
This manuscript was greatly improved by comments from Richard Connor, Will Rayment,
and three anonymous reviewers.
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Received: 6 October 2008
Accepted: 2 April 2009