USING FORWARD LOOKING INFRARED (FLIR) 

IMAGERY T.0 DETECT POLAR BEAR MATERNAL DENS 

OPERATIONS MANUAL 

BY 

Geoffrey York, Steven Amstrup, and Kristin Simac 

U.S. Geological Survey, Alaska Science Center 

101 1 E. Tudor Rd., MS 701, Anchorage, AK 99503. 

Phone: (907) 786-3928; fax: (907) 786-3636; e-mail: geoff_york@usgs.gov 

Prepared for 

U.S. Department of the Interior 

Minerals Management Service 

Alaska OCS Region 

949 East 36' Street 

Anchorage, Alaska 99508 

This study received funding from the U.S. Department of the Interior, Minerals Management 

Service Alaska OCS Region and the U.S. Geological Survey Alaska Science Center. 

September 2004 

The opinions, findings, conclusions or recommendations expressed in this report or product are those of the authors and 

do not necessarily reflect the views of the Minerals Management Semce or Geological Survey, nor does the mention of 

trade names or commercial products constitute endorsement or recommendation for use by the Federal Government. 
INTRODUCTION 

Recent research has shown that Forward Looking Infia-Red (FLIR) imagery can detect polar 

bear dens despite total snow cover over their deming habitat. FLIR imagers detect a AT or 

difference in temperature between objects in the imager's field of view. During the Arctic winter, 

the groundlsnow surface is typically cold, providing a dark background in the FLIR imager. 

Sources of heat appear as lighter or white areas. Dens, in particular, appear as small bright 

"hotspots", usually with kzy boundaries (Appendix 1). Most commonly, since bears chose 

deep snow drifts for deming, dens can be distinguished from the normally dark (cold) band of 

drifted snow surrounding them. 

This innovation has the potential to prevent human activities fiom disturbing deming polar bears 

by allowing managers to discover dens before potentially disruptive activities begin. This is 

important because expanding resource extraction in Alaska's Arctic regions may threaten the 

welfare of polar bears and their habitat. In recent years, exploration and development activities 

have expanded east and west of the original oil fields of Prudhoe Bay. Hydrocarbon extraction is 

now occurring or planned along much of the central Beaufort Sea coast. As development 

continues into the National Petroleum Reserve, the scope of expansion could include 213 of the 

northern coastal region of Alaska. Industrial activities are a potential threat to polar bears, 

especially as they might disturb bears in maternal dens (Lentfer and Hensel 1980, Stirling 1990, 

Stirling and Andriashek 1992, Amstrup 1993, Amstrup and Gardner 1994). As the number of 

humans and their activities have increased in recent years, there has been a concurrent increase in 

the number of female polar bears deming on land (Amstrup and Gardner 1994). Therefore, the 

probability of disrupting maternal deming can be expected to increase in the future. Using FLIR 

surveys to detect bears in dens could reduce or eliminate that probability. The purpose of this 

manual is to provide agency and private sector land managers with the information necessary to 

perform effective FLIR surveys to detect maternal dens. A list of personnel who can provide 

additional information is provided in Appendix 2. 
BACKGROUND 

Polar bears construct maternal dens of snow and ice throughout their circumpolar range 

(Amstrup and DeMaster 1988). Hence, denning habitat is constrained to areas of sustained snow 

deposition or drift. Many known denning areas are concentrated in a few widely scattered 

mountainous locations such as the Svalbard Archipelago, north of Norway (Larsen 1985), Franz 

Josef Land, Novaya Zemlya, and Wrangel Island, in Russia (Uspenski and Chernyavski 1965, 

Uspenski and Kistchinski 1972). 

In the southern Beaufort Sea, terrestrial dens occur throughout the coastal plain of northern 

Alaska. Previous studies suggested they were most frequent in northeast Alaska and northwest 

Yukon Territory (Amstrup and Gardner 1994). In the last decade, however, maternal dens have 

been increasingly common along all areas of the Beaufort Sea coast. Much of this region is 

currently being considered for, or is undergoing, petroleum exploration and extraction. Oil 

exploration and construction related to development generally occur during winter when 

disruption of tundra habitats and most arctic wildlife species are at a minimum. Disturbance to 

polar bear maternal dens is possible throughout this time, however, and could result in 

reproductive failure. Knowledge of polar bear den chronology provides temporal boundaries for 

management of human activities (Amstrup 1993, Amstrup and Gardner 1994). Spatial 

management, however, has been more problematic because the location of active dens has been 

known only retrospectively (visual sighting or capture of new family groups upon emergence or 

telemetry data). Sufficient snow accumulation, which is important for the establishment of 

maternal dens (Harington 1968, Lentfer and Hensel 1980, Kolenosky and Prevett 1983, Amstrup 

and Gardner 1994), is dependent on topographic features such as bluffs and banks (Belikov 

1980, Lentfer and Hensel 1980, Benson 1982). Recent mapping efforts have revealed the 

locations of potential denning areas in portions of the Alaskan North Slope (Durner et al. 2001, 

2003, Figure 1). The availability of digital maps of possible denning habitats allows land 

managers to plan their activities in order to avoid areas likely to hold dens. Sections of preferred 

habitat, however, may not be avoidable for all work scenarios. A method to detect the presence 

of active den sites is highly desirable for situations where favorable habitat and development or 

exploration overlap. In this manual, we provide guidance for using FLIR imagery to search for 

polar bear dens in habitats adjacent to human activities that could disrupt denning bears. 
The manual is comprised of two sections. First, we describe the results of tests performed to 

evaluate the effectiveness of FLIR in detecting dens. This research summary illustrates the 

technical information learned during our recent evaluation of FLIR with known polar bear dens. 

These results provide the information from which useful operational FLIR surveys might be 

developed. The second component of the manual is an outline of operational considerations 

necessary for those who conduct FLIR surveys in future management applications. This outline 

presents the critical elements of a FLIR survey, discovered during our research, in chronological 

order. The outline covers initial questions of whether FLIR is appropriate, preparing and 

conducting a survey, and post-flight tape review. The outline culminates with the process of 

making a "positive finding" decision and associated recommendations regarding images detected 

on FLIR surveys. While referencing the available research, the outline provides a "how to" guide 

for performance of FLIR surveys that will be useful in managing human activities to minimize 

impacts on deming polar bears. 
FLIR RESEARCH 

In order to test whether FLIR imagers can detect polar bear maternal dens, we needed to know 

the locations of dens. We located maternal dens by capturing female polar bears, fitting them 

with radio collars, and following them to den sites. We tested detectability of known dens by 

flying over their locations with FLIR equipped aircraft. We modeled flight and weather 

conditions most conducive to den detection with logistic regression. 

Locating Dens 

We captured solitary adult female polar bears by injecting immobilizing drugs [tiletarnine 

hydrochloride plus zolazepam hydrochloride (Telazol@)] with projectile syringes fired from 

helicopters (Larsen 1971, Schweinsburg et al. 1982, Stirling et al. 1989). Satellite and VHF radio 

transmitters were attached with neck collars (Arnstrup et al. 2000). Pregnant radio-collared 

females were followed to dens by a combination of satellite and aerial radio-telemetry. During 

FLIR surveys of radio-collared bears, we also detected several previously unknown dens. 

Surveying Dens 

We tested the effectiveness of FLIR Safire ANIAAQ-22 by flying transects over known dens. 

The Safire, which operates in the 8-12 micrometer (pm) wavelength range can, according to the 

operations manual (FLIR Systems, Inc. Portland, OR), detect differences in temperature down to 

0. lo C under ideal circumstances. The Safire was Gimbal mounted under the nose of a Bell 2 12 

helicopter. This mounting system allowed the imager to be directed independently from the 

attitude of the aircraft and in any direction below the horizontal plane of the aircraft. 

We tested the FLIR imager in transect and hover flight modes. Although we knew the locations 

of dens used for our tests, we used knowledge of the terrain to fly transects of the habitat features 

in which those known dens were located. This flight pattern simulated surveys that could be 

flown over likely habitat for unknown dens. Transect routes were flown parallel to principal 

bank habitat features. We attempted to orient the aircraft so that the prominent snow drifts likely 

to hold dens were below and to the side of the aircraft. This oblique view allowed us to focus the 
FLIR approximately perpendicular to the face of the drifts we were searching. Transect flight 

mode simulated flight patterns that might be used in operational surveys for unknown dens. 

Rather than simply flying to known locations where radio-collared bears were denning, we 

surveyed portions of bank habitats at least 1 mile either side of the known den. During 

November of 2001, we also flew transects over extensive lengths of bank habitat where no 

collared bears were known to be denning that year, but where dens had been detected in the 

previous 2 years. Surveying banks not associated with radio-collared bears provided some 

opportunity to detect dens of unmarked bears. When a known den or otherwise suspicious 

hotspot was seen on transect, we attempted to hover or circle over the spot at a variety of 

altitudes to adjust the image, and determine whether we were seeing a den or some other source 

of heat differential. After both flight modes were completed, known dens were recorded as 

detected or not. In addition to scoring detection as yes or no, we recorded the weather conditions 

at each survey occasion. Recorded weather data included ambient temperature, dew point, 

relative humidity, wind speed, wind direction, percent cloud cover, cloud ceiling elevation, 

visibility, presence or absence of blowing snow, airborne ice crystals, falling snow, fog, and 

other detectable airborne moisture. We also recorded whether or not sunlight was impacting the 

ground where we were surveying. 

In the spring, after den emergence, we attempted to visit each den located the preceding winter. 

During those visits, we recorded the size and shape of the den, the amount of snow overlying the 

lair, the nature of the habitat surrounding the den, and the slope and aspect of the drift feature 

holding the den. We also attempted to visit many of the dens in the summer after snow melt. At 

these visits, we were able to record additional characteristics of the den location and also to look 

for evidence of the deming activity that may have been left in the soil or vegetation (Durner et 

al. 2003) 
Analyses 

Data were tabulated and sorted with an Excel (Microsoft, Inc., Seattle Washington) spreadsheet. 

Analyses were performed using program S-Plus (V. 2000, Mathsoft, Inc., Seattle, WA), and SAS 

(V. 8, SAS Institute, Inc. Cary, NC). Descriptive statistics were calculated and all variables were 

cast in a Pearson correlation matrix. We tested for frequency differences in individual categorical 

variables (e.g. presence of airborne moisture or sunlight [yes or no]) between occasions when 

dens were detected and when they were not, with Fishers exact tests. Differences in values of 

individual continuous variables (e.g. cloud cover or ceiling) were tested with the Student's Ttest. 

We modeled detection of dens, in a multivariate context, with logistic regression. Although most 

FLIR images were acquired during darkness, eight attempts to detect dens were made at times 

after which sunlight had begun to light up the snow surface. No dens were detected during these 

8 attempts. Logistic regression breaks down when responses associated with a single level of a 

categorical variable are either all "successes" or all "failures." Therefore, we eliminated FLIR 

video acquired during sunny conditions and modeled detection with a logistic regression that 

applied only to non-sunny times. We used a stepwise regression procedure (Neter et al. 1996, 

Ramsey and Schafer 1997) to build a final logistic regression model (McCullagh and Nelder 

1989) describing the probability of seeing a polar bear den on FLIR video, given the weather and 

environmental conditions present at the time the video was recorded. After removing the 8 

observations associated with sunny conditions, 59 observations were available for this model 

fitting. The list of covariates considered during the model building process is provided in Table 

1. At each step a single variable could enter the model and one could leave the model. We used a 

significance level of a = 0.10 of the Score Chi-Square test incorporated into SAS Proc Logisitic, 

as the cut-off for exit and entry into the logistic model. 

Because the coefficients in logistic regression are not directly reflective of the magnitude of the 

response (like they are in linear normal theory regression, for example), we calculated Odds and 

Odds Ratios. In logistic regression the outcomes are either 0 or 1. "Odds" is simply the 

probability of getting a "1" (which is the estimate of P) divided by the probability of getting a 
"0" (which is 1 - ). In this FLIR application, the odds of seeing a den given that one was 

present (= Pr(den seen) I (l-Pr(den seen)) ), were computed. Then, to help explain the role of 

covariates in the final model, ratios of odds (odds ratios) of seeing a den at one level of a 

covariate to the odds of seeing it at the next incremental level of the covariate (e.g. odds of 

seeing a den when temperature-dew point spread = 2 versus when it equals 1) were calculated. 

Because sun was omitted from the logistic modeling, we estimated probability of identiwg an 

occupied polar bear den during sunny conditions with a 95% confidence interval constructed by 

inverting a one-sided binomial hypothesis test (Lehmann 1986, p. 93). To compute the upper 

value of the confidence interval, this method involved iteratively guessing at the value of an 

upper bound, p,, until the hypothesis &: p 2 p, was just rejected at the a level of significance in 

favor of the hypothesis HI: p < p,. For example, assuming n (here, n=8) FLIR videos were 

recorded during sunny times, and biologists could identi@ occupied polar bear dens on a of 

those n videos (here, a = 0). The upper (1-a)% confidence limit was the smallest value of p, 

that satisfied the condition for rejection of &, i.e., 

where b(x, n,p,) was the probability of observing x successes in n trials from a binomial 

distribution with probability p,, 

n ! 

b(x, n, p, = x!(n - x)! P," (1 - P, In-" - 

We recognized the possibility that interactions could have occurred between sunlight and the 

other covariates considered in our logistic model. We also recognized the shortcomings of not 

including sunlight in our overall logistic regression model. Therefore, we evaluated the binary 

response of "detected" versus "not detected" using an empirical logit transformation and a 

normal theory regression model that included sunny and non-sunny conditions. This analysis 

involved transforming the binary yeslno response (yes = den seen on video, no = den not seen) 
using the empirical logit transfornlation: f (y,) = In ( yilO'l ),where yi =l whenapolar 1-yi+o.l 

bear den was seen, and 0 when it was not seen. This transformation allowed the use of normal 

theory (linear) regression, to fit a model describing the probability of identifjing an occupied 

polar bear den given certain environmental conditions. This empirical logit transformation 

allowed inclusion of the 8 observations during sunny conditions. After the above transformation, 

a stepwise procedure was used to fit the multiple linear regression model. We used a significance 

level of a = 0.10 as the cut-off for exit and entry into the model. Odds ratios again were 

computed to aid interpretation of coefficients in the final model. 
Results 

During this study we located 19 polar bear maternal dens on land by radio telemetry. Bad 

weather, poor quality radio fixes, dificult terrain, and a malfunctioning tape player prevented us 

from securing FLIR images at 4 dens of radio-collared polar bears. During attempts to view the 

15 remaining dens, we observed 12 previously unknown hotspots that we concluded, either in 

flight or upon subsequent review of FLIR tapes, were polar bear dens. Dens (and targets 

presumed to be dens) appeared as small bright (hot) spots, usually with soft boundaries, within a 

normally dark (cold) band of drifted snow (Appendix 1). Spring and summer surveys confirmed 

that 3 of the unknown hotspots were not polar bear dens. Thermal differentials we detected at 

these sites were the result of 1) an empty steel barrel, and 2) a large boulder partially embedded 

in an unstable permafrost bank and 3) a piece of sloughed tundra lying partway down a 

permafrost bank. We failed to obtain evidence confirming whether a 4h unknown hotspot was a 

den. This hotspot had all the earmarks of a den, but despite 2 winter images, we were unable to 

return to this site in either spring or summer to search for evidence of polar bear use. 

We surveyed the other 23 dens or hotspots on 67 occasions (1 to 7 times each). The number of 

viewing occasions was inversely proportional to the distance of the den from the home base of 

the helicopter used for FLIR surveys. Four dens (1 7%) were never detected with FLIR. Two of 

these were visited on 2 occasions; the other two were visited only once. One den visited twice 

was detected both times. Two dens visited once each were detected on those single visits. 

Detection of the other dens was mixed. Figure 1 summarizes the frequency of detection for the 

23 dens surveyed at least once. 

Univariate Comparisons 

We used the Student's two-sample t-test to compare the continuously distributed covariates wind 

speed, temperature, temperature dew-point spread, cloud cover, cloud ceiling height, and 

maximum reported visibility, at times when we detected known dens versus times we didn't 

detect them. We also compared depth of snow over the lairs of dens that were not detected to the 

depth over dens that were detected. When evaluated singly, in the two-sample t-context, only 

wind speed and temperature dew-point spread differed significantly between detection and nondetection events. The mean wind speed (1 1 ktslhr) on occasions when we didn't see dens was 
significantly higher than on occasions when we did see dens (6 ktslhr) (t = 2.897, d.f, = 65, P = 

0.005 1). Similarly, the mean spread between temperature and dew-point on occasions when dens 

were not seen (2.56 "C) was significantly narrower than the mean spread (3.01 "C) when dens 

were seen (t = 2.89 1, d. f. = 65, P =0.0052). 

It stands to reason that the depth of snow over dens is directly related to the degree to which the 

heat from a bear is insulated fiom the snow surface. The range of depths recorded for dens in this 

study, however, was apparently below any threshold that prevents detection by FLIR. Although 

the differences were not significant (t = -1.001, d.f. = 18, P =0.383), the mean depth over 

detected dens was 40cm while the mean depth over dens that were not detected was only 3 lcm. 

Also, the greatest depth (96cm) was recorded over a den that was detected both times it was 

surveyed. 

Two covariates were recorded simply as present or absent at each FLIR occasion. airborne 

moisture included blowing snow, falling snow, fog, mist, or ice crystals. If any of these 

conditions, either singly or in combination, were detectable, Airborne Moisture was recorded as 

yes. If none were present, Airborne Moisture was recorded as no. Similarly, if the sun was above 

the horizon and shining on the snow surface (even with cloud cover present), the variable Sun 

was recorded as yes. Airborne Moisture was detectable on 12 of 23 (52%) occasions when dens 

were not seen and on only 15 of 44 (34%) occasions when they were seen. A Fishers Test 

contingency table, however, suggested this difference was not significant (2 = 2.06, d.f. = 1, P = 

0.152) indicating that the presence of air moisture didn't, by itself, explain detection of known 

dens. Sunlight was present on 8 of 23 (65%) occasions dens were not seen, and on none of the 

occasions dens were seen. This difference was highly significant (2 = 17.38 d.f. = 1, P = 

0.00003). The probability of seeing an occupied polar bear den on FLIR video recorded in 

sunlight was estimated to be 0, with an upper 95% confidence bound of 0.3 13 (Table 2; 

(Lehmann 1.986, p. 93)). 

Modeling Detection 

Some insights regarding the ability of our measured covariates to explain detection by FLIR 

were obtained from the above individual comparisons. Recognition of possible interactions 
among our covariates, however, mandated modeling approaches in which all covariates were 

eligible to enter. The final logistic regression model for the probability that an occupied polar 

bear den was seen on the FLIR video recorded during non-sunny times was, 

jj= exp[-2.8576 + 1.1237(spread) + 1.5692(air - moist = O)] 

1+ exp[-2.8576 + 1.1237(spread) + 1.5692(air -moist = O)] ' 

Standard errors for coefficients in the final model were 0.5401 for spread and 0.6846 for 

air-moist. The odds ratio for spread was 3.08, indicating that for every 1 degree ("C) increase in 

the difference between temperature and dew point, we were 3.08 times more likely to see the 

den. This Odds Ratio was calculated as: 

The probability of detecting a den when the spread = 1 is : 

jj = exp[-2.8576+1.1237(1)+1.5692(air-moist=O)] - 

1 + exp[-2.8576 + 1.1237(1) + 1.5692(air - moist = O)] 

The odds of an event is the ratio of the probability that the event occurs to the probability that the 

event does not occur, so the odds of detecting a den when spread = 1 is : 

.459 = 0.848. 

1 - .459 

However, when the temperature-dew point spread is increased to 2"C, the probability of 

detecting a den is: 

jj = exp[-2.8576 + 1.1237(2) + 1.5692(air - moist = O)] - - 

1 + exp[-2.8576 + 1.1237(2) + 1.5692(air-moist = O)] 

The odds of detecting a den when the spread = 2 is : 

So, the odds ratio for a 1 unit increase in spread from one to two is: 
Interestingly, odds ratios are easily calculated for each one unit increases in a predictor variable 

by simply "exponentiating" the coefficient value of that predictor variable (raising e to the value 

of the coefficient), e.g. = 3.08 . 

Similarly the odds ratio for air moisture was exp(1.5692) = 4.803, indicating that the odds of a 

trained biologist detecting a den was approximately 4.8 times higher when there was no visible 

moisture in the air at the time the video was recorded when compared to times with moisture in 

the air. 

Parameter estimates, odds ratios and 95% confidence intervals for the odds ratios are presented 

in Table 3. Table 4 contains descriptive statistics of the variables in the final logistic regression 

model. Figure 2 contains the probability of seeing a polar bear on the FLIR video at various 

levels of the variables in the final logistic model. 

In order to incorporate the sunshine covariate into a comprehensive model, we transformed the 

binary response using the empirical logit. The final normal linear regression model for the 

probability that an occupied polar bear den was detected on the FLIR video was, 

f (y) = -5.3273 + 3.3418(sun = 0) + 0.8555(spread) + 1.1666(air - moist = 0). 

The standard error for sun was 0.7341. The standard errors for spread and air-moist were 0.3802 

and 0.4699, respectively. Coefficients for spread and air-moist were approximately the same size 

in this model as they were in the final logistic regression model. The approximate odds ratio for 

spread was estimated to be exp(0.8555) = 2.35 (this odds ratio is "approximate" due to the 

constant of 0.1 in the empirical transformation). The approximate odds ratio for air-moist was 

3.21 1. The approximate odds ratio for sun was 28.27, indicating that under similar temperaturedew point spread and no moisture in the air, the odds of detecting a den during non-sunny times 

was 28.27 times higher than during sunny times. Figure 3 contains plots of the probability of 

detecting a polar bear den on the FLIR video, as a function of variables in the final normal leastsqwes regression model. Parameter estimates, standard errors, and p-values for variables in the 
final normal least-squares regression model are presented in Table 5. Table 6 contains 

descriptive statistics of the variables in the final normal regression model. 

Discussion 

Kingsley et al. (1990) reported that thickness of snow, ambient temperature, wind, and sunlight 

prevented ringed seal lairs from being detected consistently enough to allow census by FLIR 

over sea ice habitats. We abandoned attempts, early in this study, to detect dens in the ice 

environment because of the array of competing heat signatures. FLIR systems detect a difference 

in temperature between adjacent sites in the field of view. The ocean is a relatively hot 

environment in the Arctic. Cracks, holes, and pressure ridges created an infinitely variable 

mosaic of hot, warm, and cold spots in the FLIR screen. Early in the pilot phases of this study, 

we captured a very clear image fiom the den of a collared bear high in a pressure ridge of land 

fast ice. Extremely cold weather and tight ice, along with ideal atmospheric conditions, 

apparently contributed to that successful detection, because upon later visits, we were unable to 

distinguish the den fiom surrounding hotspots. We also failed to differentiate the heat signature 

of another den on land fast ice that earlier had been visually observed. Similarly, we consistently 

failed to detect the dens of 2 radio-collared bears denning on drifting pack ice during this study. 

The heat signatures fiom these dens may have appeared on the FLIR screen. Due to the 

abundance of competing hotspots, however, we were unable to know with any certainty whether 

the dens were among the visible heat signatures. 

Although FLIR may not be satisfactory for distinguishing dens on the sea ice, it was effective in 

detecting dens on land. Bears denning on land are generally surrounded by colder and more 

uniform substrates than seals or bears occupying subnivian lairs at sea. Polar bears also are larger 

and presumably emit more heat than ringed seals. The potential thermal contrast of denned bears, 

the uniform backdrop of land and snow, and the FLIR equipment used in this study, combined to 

create a useful tool for detecting polar bears in their dens in early winter-before construction 

projects and seismic surveys normally occur. Fortunately, it is those dens on land that are the 

greatest management concern related to industrial development of the north. 
We recognize our FLIR surveys, under the conditions they were carried out, were not 100% 

effective in detecting dens. We do not expect that the FLIR technology used for this study will 

detect all dens regardless of ambient conditions. Future improvements in FLIR technology 

should be pursued and retested for this application. 

However, tempered with the knowledge we provide here, we believe FLIR has an important 

place in management of human activities that could adversely affect deming polar bears. The 4 

dens (17%) we failed to detect during our study were visited a total of 6 times. The first den was 

initially visited inmediately following a blizzard with extensive blowing and falling snow. 

Surface snow temperatures had not stabilized prior to the flight and the ground surface was 

extensively mottled with a wind-row pattern of alternate bands of warm and colder snow. Wind 

speed did not enter our final models of detection. Nonetheless, the wind-row effect on the snow 

surface often was apparent even when wind speeds were below those that result in obvious 

blowing snow. This may partially explain the T-test suggesting dens were less detectable under 

elevated wind conditions. Additionally, this den survey was conducted despite a cloud ceiling of 

only 400 feet and a temperature-dewpoint spread of 2.2 "C. The only other time we were able to 

visit this den, the sun was shining. Clearly, neither of these surveys maximized our odds of 

detecting this den. The second and third dens that went undetected were visited only once each. 

Those flights both occurred despite airborne moisture visible in the FLIR. Our detection model 

verifies we were nearly 5 times less likely to see either of these dens than if we had visited them 

on days without airborne moisture. The fourth den that escaped detection was visited twice. On 

the first visit, the temperature-dew-point spread was 2.2 "C, less than the mean value for dens 

that were not detected. The second visit, however, occurred under conditions that should have 

been favorable for detection-yet we were not able to detect the den. 

We cannot know now if added visits under conditions maximizing the odds of detection would 

have resulted in successful detections of these 4 dens. We do know, however, that 5 of the 6 

visits to these dens were during weather and snow conditions that compromise effectiveness of 

FLIR. Therefore, it is reasonable to think our success rate could have been higher under more 

suitable conditions. 
Logistical constraints prevented acquisition of sufficient data to quantify the probabilities of false 

positives (calling a thermal signature a den when it is not). It is comforting, however, to 

recognize that despite flying hundreds of kilometers of FLIR survey, we identified only 3 such 

hotspots. We are confident that subsequent visits to these sites would have resulted in their 

removal fiom our list of suspected dens. Hence, had such hotspots occurred in habitats that were 

proposed for disturbance, it is likely that multiple surveys would have revealed they were not 

dens before expensive management measures commenced. Likewise, the one unknown hotspot 

we were unable to revisit for confirmation purposes, would have been revisited in a real 

management situation. Our experiences in this study suggest that the risks of false positives are 

low. 

Because of the large areas over which they roam and their low overall numbers, general surveys 

of polar bears or polar bear dens would not be practical even with new FLIR technologies. We 

know, however, that denned polar bears occur primarily in steep bank faces along streams, 

lakeshores, and coastlines of the mainland and some offshore islands. Further, those faces have 

been identified and mapped across a large section of Alaska's north slope (Durner et al. 2001, 

Durner et al. 2003). The combination of mapped den habitat and modern high sensitivity FLIR 

imagery provides the first real tool for detecting polar bears in dens early enough in winter to 

alter the paths of human activities in order to protect denning bears and humans. With denning 

habitat either mapped or clearly described, many human activities that might affect denning 

bears could be routed around those preferred habitats, avoiding the possibility of negative 

impact. If a road or other development "must" traverse pieces of den habitat; FLIR surveys of the 

development comdor can help assure minimal population level effect on denning polar bears. 
FLIR OPERATIONS 

I. Is FLIR necessary or appropriate to address your management issue? 

A. Like any tool, FLIR is not appropriate for all situations. It is best used under 

circumstances where disturbance activities are expected to occur adjacent to suitable 

bank habitat in remote locations. There is little utility in conducting a FLIR survey in 

areas of flat tundra devoid of banks or other suitable habitat. FLIR is also not suitable for 

detection of dens on sea ice (see previous section). A proposed ice road following coastal 

bank habitat for many miles or running adjacent to barrier islands would be a good 

example of an appropriate FLIR project. If you think FLIR may be suitable for your 

project, consult the denning habitat maps created by USGS (Durner 2000). Layering your 

proposed activities over the available denning habitat will illustrate areas of possible 

conflict. Projects can use these maps in the early stages of planning to simply avoid 

habitats likely to hold denning bears. Such avoidance could eliminate the need for 

additional mitigation measures such as FLIR. 

B. If the proposed disturbance activity cannot avoid all preferred denning habitat, or if 

such avoidance would be extremely expensive, FLIR could be used to examine the 

habitat segments at risk. It is important to recognize that other tools may also be 

applicable depending upon the situation. For example, if the "at risk" habitat segments 

are relatively small (the banks on a small coastal island, for example) trained dogs might 

be brought in to detect polar bear maternal dens. Although sample sizes were small, 

appropriately trained dogs have been successhlly used to confinn the presence of polar 

bear dens in northern Alaska (Perham 2002). Highly trained scent dogs may be very 

effective in detecting dens, and because they key in on the scent of polar bears, they are 

not likely to mark "false positives" (hot spots that look like, but are not dens). Working 

with dogs, however, has its own logistical limitations. Extreme temperatures limit the 

amount of time dogs can work without rest and warming, and long distance transport to 

cover more extensive areas is logistically impractical. 
11. Planning a survey 

A. Obtain or create maps of the activity area and proposed developments. 

B. Obtain bank denning habitat maps fiom USGS (Figure 1 and Appendix 2) available 

through the following web site: 

- summaries/polar - bears - sis/ma~gingdens.htn~. 

C. Overlay the proposed activities on the habitat maps and note areas of potential 

conflict- where development occurs within 2 miles of designated bank habitat. 

D. Select bank habitat areas of concern, divide those sections into transects, and assign 

numbers for each transect leg (Figure 2). This will insure that the entire habitat is 

surveyed and will ease video review. 

E. Make a list of GPS waypoints for the start and finish of each transect and create a 

map of the habitat and transect lines as noted above. Provide copies to all crewmembers 

and review prior to the mission. 

F. Choose a survey window that is late enough in the year for bears to have entered 

dens, but early enough to maximize darkness and minimize snow cover over the dens. 

(The second week of December through mid-January should be ideal, depending on 

weather conditions). 

G. Allow enough tinle to survey the entire area once, return for some point verifications, 

and account for potential weather days. Once you depart the study area, it is costly to 

arrange a follow up effort. 
111. Personnel requirements 

A. To conduct FLIR missions for the purpose of detecting polar bear dens, it is 

recommended to have a FLIR operator and two observers. 

B. The operator should be experienced with the FLIR equipment (make/model) available 

for use and have some experience using FLIR for wildlife or surveillance under winter 

conditions. 

C. Ideally, the operator, pilot, and the two observers will have some familiarity with 

Arctic topography. Bank habitat drifted over with snow and other nuances unique to 

fiozen patterned ground make the use of both FLIR and video imagery challenging. 

Navigating polygon tundra can be demanding any time of year and is only complicated 

by snow and ice. The entire crew should o.btain copies of existing FLIR video to 

acquaint, or re-acquaint, themselves with the target imagery and mission techniques. 

(Appendix 1) 

IV. Equipment requirements and settings 

A. To date, FLIR surveys have been conducted with a FLIR Safire I1 (ANIAAQ-22) 

thermal imaging system leased fiom Alyeska Pipeline Service Company complete with 

four video monitors (two up fiont and two in rear), and a Sony mini-DV tape recorder. 

This equipment is stored with Air Logistics, Inc. in Fairbanks, AK. 

B. Helicopter choice is dependant on availability and required capabilities. Our testing 

efforts utilized a Bell 21 2 outfitted for IFR flight. Since FLIR work should be conducted 

during VFR conditions (see above), a single engine, single pilot aircraft would also work 

well and has advantages of reduced cost, increased maneuverability, and reduced noise 

levels. The primary disadvantage to a non-IFR aircraft is limited operational time due to 

darkness. Also, weather in the Arctic can change quickly, and the limited VFR windows 

can close suddenly requiring IFR returns to base camp. 

C. A Garmin or comparable GPS should be used for flight track logging. All clocks, 

including the internal FLIR clock, should be synchronized with the GPS prior to any 
survey. 

D. Make certain the video recording unit is wired into the aircraft communications 

system to record all flight conversations during FLIR transects. This will be imperative 

for future video analysis! 

E. During our survey development, the FLIR was set to Cage position at the beginning 

of each transect with the default of: -30 degrees of elevation and 0 degrees azimuth. The 

following settings were also used: Cross Hairs and Reticules were turned off, Polarity set 

to white hot, and Gain set to automatic. 

F. Use a professional video editing tape deck with frame-by-fiame capabilities for tape 

review. Review is best accomplished using a large format video projector with a 

projection screen, or using the best available and largest video monitor. Video should be 

reviewed at the close of each flight session. We detected some dens and hotspots only 

during tape review. The pace of action, and the vibration caused by the rotors, can result 

in lack of focus on the FLIR monitor during survey flights. The reviews of recorded tapes 

each evening after flights is a critical part of the den detection process as it allows the 

field crew the option of revisiting suspect sites during the next mission for clarification. 

As stated earlier, hot spots identified after the crew has returned home are often 

impossible to revisit logistically. 

V. Survey Procedures 

A. By necessity, surveys will be conducted during the darkest time periods of the year, in 

conditions of predominantly "civil twilight". 

B. There must be adequate light or contrast upon reaching the target area so that the 

flight crew can visually reference the ground and features of interest. If it is too dark, or 

flat light conditions exist such that you cannot distinguish bank habitat or barrier islands, 

you cannot effectively conduct a FLIR mission. Therefore, FLIR missions must be 

conducted during the civil twilight of the Arctic winter or during clear moonlit nights. It 

is important to note that surveys conducted after mid-February will be marginally 

successful even if conducted at night. This is due to the solar warming that occurs during 
daylight which results in considerable IR re-radiation fiom heated surfaces. The mottled 

pattern of reradiating surfaces of ice and snow profoundly reduces the ability to 

distinguish dens fiom other warm targets (Appendix 1). 

C. Remember, polar bears den in areas of snow accumulation or drift- you will be 

working in a white on white environment. Weather can also delay or terminate a FLIR 

mission. Ideal conditions for surveying would be clear, calm, and cold. If there is blowing 

snow, any form of precipitation, or other sources of airborne moisture- use of FLIR is not 

advised. Our models of how detection probability varied with environmental conditions 

revealed that the Odds of detecting a den: 

1. Increased 3X for every one degree (C) increase in Temperature Dew-point 

spread. 

2. Were 4.8X higher when airborne moisture (snow, blowing snow, fog etc.) was 

absent than when it was present. 

3. Were approximately 28X higher in darkness than after sunrise. 

Although not selected by the model, wind speed also appeared to be a significant factor. 

The mean wind speed (1 1 kts/hr) on occasions when we didn't see dens was significantly 

higher than on occasions when we did see dens (6 kts/hr) (t = 2.897, df = 65, P = 0.005 1). 

D. Crew needs and duties: 

1. The team leader should hold a briefing prior to each mission covering plans 

for that day and any comments fiom previous efforts. The FLIR team will consist 

of an operator and two observers. 

2. The operator is responsible for the FLIR unit while in flight. They should 

study the FLIR operation manual for the specific unit in use and become familiar 

with its functionality, calibration, and use. Prior to a mission, the operator should 

check that the equipment is operational, the latitude and longitude are displayed 

on the monitors, and that the internal clock is synchronized with the GPS unit. 
3. The two observers should familiarize themselves with the target area (maps) 

and with IR imagery of the Arctic landscape during winter @re-survey video 

review). It will be their job to help keep the aircraft and FLIR over targeted 

topography. They will also be looking for surface features that may explain a hot 

spot (dirty snow, exposed soil, ice, etc.). One observer will be designated as the 

primary data collector- maintaining the flight data sheets and other field notes, 

and monitoring the status of the GPS used for recording the ground track of the 

survey flight. The pilot(s) will also bction as additional observers as conditions 

allow them to participate. 

E. Take off procedures: 

1. After the aircraft engines have started, turn the FLIR unit on and allow it to 

warm up. It will go through a series of self-tests in the process. DO NOT POWER 

THE FLIR UNIT UNTIL AFTER THE HELICOPTER HAS STARTED ITS 

ENGINE(S). 

2. Using the calibration menu, adjust the grayscale as per the manual. 

3. Stow the FLIR prior to taking off. LEAVE POWER ON. 

4. Start the Garmin for flight track recording and begin flight data sheet entry. 

F. Surveying the habitat: 

1. Upon reaching the target area, you will need to line up for your first transect 

leg. Weather conditions at the time of the survey will often dictate the direction of 

travel and may determine minimum speeds and elevation. However, try to survey 

each transect in two directions if conditions permit. The view angle can be critical 

in detecting dens and this will provide you with some good additional data for the 

video review sessions. 

2. The aircraft should position itself so that it is somewhat abeam, or offset, of 

the habitat feature. This allows the FLIR to aim directly at the face of the bank 

feature. You will fly parallel to the bank so that the FLIR is looking into the face 

of the snowdrift. This will pennit the FLIR to capture the critical habitat in the 
video window while allowing the observers to visually scan the terrain feature of 

interest. The operator will have to adjust the imager during the transect to remain 

on target. 

3. The elevation should not exceed 800 feet and the speed should not exceed 40 

knots. 

4. If the aircraft is positioned well, the FLIR image of the bank habitat will nearly 

fill the screen. If you are seeing too much of the surrounding habitat (tundra or sea 

ice) in the monitor, you may want to lower the altitude of the survey. Ideally, the 

bank habitat will fill the video monitor with little surrounding habitat showing. 

5. Aircraft position and the FLIR view angle can play a significant role in the 

video quality. A compromised view angle can result in poor image contrast 

(causing the screen to darken or lighten) making it diflficult, if not impossible, to 

detect faint heat signatures. Again, make sure the FLIR unit is looking into the 

face of the bank. 

6. All transects begin in wide field of view (WFV) and adjustments are made to 

the azimuth and elevation as needed to stay on target. 

7. During all transects, repeatedly switch back and forth between IR and video 

modes. This will help the operator stay on the habitat feature and aid in the 

interpretation of the video during review at the close of the mission. This method 

is also critical when you are hovering or circling over a target of interest. It is 

important, however, that toggling between IR and video is completed rather 

quickly to insure that all portions of the habitat are viewed in the IR mode. Video 

mode will not detect heat signatures. 

8. When a hot spot is noted, mark the position with a GPS and make a visual 

record of the area. If conditions permit, immediately pull into a hover abeam of 

the suspect spot. Otherwise, upon completion of the transect, return to all 

observed hot spots for hover verification, additional FLIR video, and to obtain an 
accurate GPS location for fbture reporting and mapping. Gradually pull into a 

hover over the location while maintaining a minimum of 200 feet elevation. Make 

certain to switch periodically between FLIR and Video modes during this 

procedure, holding in each mode for at least five seconds. The pilot(s) and 

observers must use this opportunity to visually examine the ground for any 

surficial disturbance (dirt, debris, and excavation) that may explain the hot spot. 

This will also provide an opportunity to use the Narrow Field of View (NFW) 

functionality to zoom in with the FLIR. Also, try to get as many different view 

angles as possible on the tape while you are hovering. All of these variations 

(Hover, Video, Visual, and NFW) provide different and necessary information for 

later interpretation. 

9. Finally, and of critical importance: obtain the best data possible for each 

hotspot as efficiently as possible. You must always remember to minimize 

disturbance to the denning bear. 

G. Landing Procedures: 

1. Cage and stow the FLIR unit prior to landing. DO NOT TURN POWER OFF. 

2. After landing, and prior to helicopter engine shutdown, power down the FLIR 

and Garmin units and note the time on the flight data sheet. 

VI. Tape Review 

A. Experienced FLIR personnel are required to successfblly interpret the video footage. 

All hot spots are not necessarily of interest. When conducting FLIR video reviews, it is 

difficult to have too much information from the field. Some questions to consider when 

reviewing FLIR include: 

1. Is this likely denning habitat? Is this bank habitat? Is there adequate snow 

depth? 

2. Does the hot spot fall within an appropriate area of the bank? Is it too high on 

the drift or too low? 
3. Is the hot spot associated with a crack or anything visible on the surface (dirty 

snow, tundra, shape of a drift or other snow feature, etc.)? Does it have a linear 

character, or is it part of a larger linear feature? 

4. Is the hot spot similar in size and shape to other known den hot spots 

(Appendix I)? 

5. Does the hot spot stand out as 'different' fiom any surrounding spots or heat 

sources? (This is not a solid indicator- dens can be associated with other "warm" 

features that can mislead the reviewers.) 

B. Review FLIR tapes as soon as possible after each flight, while still in the field, and 

with the crew that completed the task. During this review, update the flight data sheets to 

include as much information as possible fiom the video, audio, and your collective 

memory of the mission. It can get hectic in the aircraft and it is subsequently easy to omit 

information while flying. When reporting on FLIR surveys, it is difficult to have too 

much information fiom the field. 

C. Examine all tapes thoroughly and with a critical eye. With every possible hot spot, 

remember to ask the above questions. It is critical to correctly identify all dens, but there 

are also real consequences for incorrectly identifying a hot spot as a den. 

VII. Verification 

Any hot spots of interest noted during the tape review, or hot spots needing additional 

verification should be revisited on subsequent days under good environmental conditions. During 

these secondary transects, it remains imperative to obtain ample transect and hover footage in 

both IR and standard video. To diagnose the hot spot, observers should once again scan for any 

signs of surface abnormalities (rocks, driftwood, bare soil, etc.). 
VIII. Final Decisions 

Ultimately, yo^ will have to make a decision regarding all of the hotspots noted during a FLIR 

den survey. The information provided thus far should assist in this procedure; however, there 

will be a subjective component. Tests showed conclusively that nayve observers could not be 

expected to make sound decisions regarding the nature of hotspots identified in FLIR. Hence, all 

crewnlembers should study existing tape records prior to engaging in fieldwork. The entire 

observation crew should also work as a team during tape review processes in order to render the 

best and most objective decisions possible regarding detected hotspots. 

Summary 

Prior to embarking on a FLIR mission, make certain you have adequate time, personnel, and prefield planning. During the planning stages, map all development areas and polar bear denning 

habitat within the region of interest. Refer to these maps when conducting the FLIR surveys and 

provide abundant related data such as transect direction, altitude; ground speed, weather, and 

geographic place names in your field notes and on the voice record,. You must have experienced 

staff on hand and adequate aircraft availability (time for initial survey work and for verification 

of select spots). 

Verify all hotspots seen during transects while in the field. Make every attempt to confirm or 

deny all hotspots of interest through: transect over flights at an elevation not to exceed 800 feet, 

hovering, video and IR footage, and outside observations of the physical environment. Tapes 

should be reviewed as soon as possible following the mission, preferably that evening. If 

possible, tape review should be conducted using a projection device that will enable viewing on a 

large format silver screen. Any "new" hotspots detected during video review must be revisited 

while the survey team is in the field. FLIR cannot be successfblly applied in a hurried manner. 

Experienced FLIR operators and observers are critical to the success of this technique. Observers 

need to have knowledge of the Arctic landscape in winter to effectively evaluate what they are 

seeing outside the aircraft and on the video monitor. While conducting FLIR survey transects, 
flip frequently between IR and video to maintain bank position and give video reviewers 

adequate perspective. When a hot spot of interest is located: take several waypoints and clearly 

indicate your geographic location, datehime, altitude, and any additional notes. Make a vertical 

hover over all significant hotspots to obtain the most accurate location. This also gives the 

pilot(s) and observers a final chance to discern any obvious surface features or an open hole. 

This can be achieved at an altitude of 200 feet or greater. Again, make certain that sufficient IR 

and video footage is taken at all hot spots of interest. 
Polar Bear Maternal 

Den Habitat 

elevation scale 

Mikkelsen Bay 

I 

-A high 

FIGURE 1: An example form the USGS polar 

habitat is shaded yellow with red outline. 

bear denning habitat map (Dumer 

- 

2000). Possible den 
I Area of concern 

FIGURE 2: This represents a proposed ice road overlain on a den habitat map. The area of concern 

(determined by U.S. Fish and Wildlife Service) is estimated by the shaded circle. An example of a 

transect layout is also provided for Tigvariak Island. The lines indicate relative position only, as you 

would actually follow the habitat in your survey effort. 
APPENDIX 1 

FLIR IMAGE CATALOG 
Figure 1: This is a FLIR image of coastal bank habitat. You can clearly see the polygon tundra 

on top, a cool dark band of deep snow drifted against the bank in the middle, and the relatively 

warm, bright sea ice at the bottom of the image. This would be ideal polar bear den habitat, and 

from the quality of the image, and ideal day to conduct a FLIR mission. 
Figure 2: A less clear view of similar bank habitat. Despite the apparently hazy image, the bank 

feature is still quite apparent. 
I Tundra I 1 

Sea Ice 

Figure 3: FLIR image of a coastal bank under conditions where moisture was present in the air. 

You can still make out the bank habitat and see some of the polygon tundra. 
Figure 4: A classic FLIR den signature in narrow field of view (zoom). You can clearly see the 

soft warm glow in an otherwise dark area of drifted snow. 
Figure 5: The red circle surrounds the faint den signature fkom a known bear den along the bank 

of a barrier island. Habitat features are very clear in this image. 
Figure 6: The faint glow of a known polar bear den along coastal bank habitat. Note warm sea 

ice to the left and tundra to the right of the dark snow drift along the bank. 
Figure 7: The heat signature from a known polar bear den. This image is a little more difficult to 

discern the habitat features. 
Figure 8: Faint image of a known den during a mission with some air moisture present. 
Figure 9: Two images of known dens in the narrow field of view mode of FLIR (zoom). In the 

lower image you can actually see what appears to be the entrance hole. 
Figure 10: Two images of known dens in the narrow field of view mode of FLlR (zoom). The 

shape of the heat signature in the lower image actually reflected the internal geometry of the den 

structure. 
Figure 1 1 : Dens are not always obvious as seen in these two FLlR images. The first image 

shown a den taken with an uncalibrated imager in poor weather conditions (It is surprising this is 

visible at all). The second image was taken under poor conditions (moisture visible in the air). 
Figure 12: As noted in the protocol, the presence of air moisture is one of the most significant 

factors which limit FLlR effectiveness. The three images above are fiom the same den on 

different days and conditions. The first image is under good conditions and the second two were 

taken with fog (middle) and snow (bottom). 
am". .. ...a " 

Figure 13a: Conditions can also change during a mission. The next two pages show images taken 

of the same dens on the same day. The difference is due to the presence of moisture in the air on 

the afternoon transects. For both figures the morning flight is above and the afternoon below. 
Figure 13b: Morning transect above, afternoon with moisture present below. 
Figure 14: Trwect orientation can also effect den detection with FLIR. In the above images the 

same den is surveyed first fiom East to West (top) and then fiom West to East (bottom). 
Figure 15: As mentioned in the protocol, polar bears den in drifts along banks. Hence, the 

location of a perceived hot spot is critical. The hot spot in the top photo is clearly on the tundra. 

In the middle photo, despite the poor viewing conditions, we see much the same thing. On closer 

inspection, this spot is actually a grazing caribou (bottom). 
T N 7i0 6.82' Lffl U 154%. 78' 8S. 6% -4El 17-814 13:lO: 2% 1 

Figure 16: Be wary of hot spots near the bottom of banks or associated with linear features. The 

top image shows a beaded crack you would expect to see on sea or river ice. The middle photo 

shows several hot spots that are clearly below the bank drift and associated with se or river ice. 

The bottom image shows a classic hot spot, but it is associated with a linear feature and is on the 

flat sea ice where there is inadequate snow drifting. 
Figure 17a: Use a combination of video and FLIR to help weed out suspicious hot spots. The top 

image shows what appears to be a promising hot spot. The bottom image indicates the spot is 

merely the exposed soil of an eroding bank. The spot is also very high on the bank. 
Figure 17b: The same can be seen in this series of FLIR and video imagery. The hot spot again 

appears to be exposed soil or a rock and is located much higher on the bank than one would 

expect for a polar bear den. 
Figure 18: The video/FLIR combination does not always provide the answers as can be seen in 

this series of images. In this case, it would be best to hover down near the sights and look for any 

visual cues by looking directly out the window. These would be reasonable hot spots to identify 

as potential dens if there was no other evidence for the heat signatures. 
Figure 19: The detrimental effects of sunlight can be clearly seen in these images. Anything that 

sits above the surface will begin to rapidly warm with the least amount of solar radiation. Such 

competing hot spots make it virtually impossible to detect dens under these circumstances. The 

top image shows vegetation along a river bank and the bottom image is the same taken in narrow 

field of view- branches are clearly visible. 
I"."".. L .""".I 

Figure 20: Sunlight can also make the landscape uniformly warm thereby lightening the FLIR 

image and making it more difficult to discern features and potential dens. Note the lack of 

contrast in the deep snow drift along the bank in these figures. 
1 70' 5.99' LON U 145O40. 38' -51 So!& -4151 15-01-01 16:12: 1% 1 

Figure 21: Very bright spots located in suitable habitat may indicate open dens as is evident in 

these images. In the bottom image you can actually see the footprints of a bear that recently left 

the den. Abandoning dens mid-winter is not uncommon although the reasons for this are poorly 

understood. 
Figure 22: Man made objects, such as buildings and vehicles, are easily discernible with FLIR 

and make excellent targets for practice and FLIR calibration as you depart the airfield and head 

towards the target area. If you cannot see man made targets with the FLIR, something is wrongcheck the weather and your equipment before proceeding any Mer! 
Figure 23: Surprisingly, polar bears themselves are also quite visible with FLIR! 
APPENDIX 2 

FLIR CONTACT LIST 
U.S. Geolopical Suwev, Alaska Science Center: 

101 1 East Tudor Road, Anchorage, AK 99503 

Steve Amstrup 

Polar Bear Research Project Leader 

FLIR study design/Observer 

Ph.#: (907) 786-3424 

Email: steven~amstmp@usgs~o_v 

Geoff Weston York 

Polar Bear Research Biologist 

FLIR Operator 

Ph#: (907) 786-3928 

Email: neoffyo&@usgsgo_v 

George Durner 

Polar Bear Research Biologist 

Den Habitat Maps/FLIR Observer 

Ph#: (907) 786-3366 

Email: george-d-rausgs. gov 

Kristin Simac 

Polar Bear Research Biologist 

FLIR Video reviewer 

Ph#: (907) 786-3942 

Email: kristin~simac@usgs.~~ 
Air Logistics Alaska: 

191 5 Donald Avenue, Fairbanks, AK 99701 

Jeff Reed 

Chief Pilot 

Phone: 1 -888-CHOPPER 

Fax: 907-452-4539 

e-mail: jreed@airlogak.com 

FLIR Systems, Inc.: 

16505 SW 72nd Avenue, Portland, OR 97224 

Marshall Grose 

Ph#: (503) 372-683 1 

FAX#: (503) 372-61 66 

Sales: 1-800-322-373 1 

Web site: http://www.flir.com