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[NASA-CB- 180081) ESTIHATIYG POPULATIGN SIZE B8 9 -2 46 87 

OF PYGOSCELID PENGUINS FBOH TPI DATA Final 

Report (Michigan Univ,) 45 p CSCL 06C 

Unclas 

G3/43 02098 32 
ESTIMATING POPULATIGK SIZE OF 

PYGOSCELID PENGUINS FROM TM DATA 

Charles E. Olson, Jr 

Mathew R. Schwallerl 

Paul A. Dahmer2 

1x0~ with SklC, McLean, Virginia 

2Now with ERIN, Ann Arbor, Michigan 

FINAL REPORT 

to the 

National Aeronautics and Space Administration 

under 

Contract NAS 5-28755 

The University of Michigan 

School of Natural Resources 

Remote Sensing Laboratory 

Ann Arbor, MI 48109-1115 

August 1987 
ACKNOWLEDGEMENTS 

The research described in this report was specifically concerned with 

developing satellite remote sensing methods to estimate the population size 

of Pygoscelid penguins on their nesting sites. This research was motivated 

in part by observations which found that penguins are one or' the most 

sensitive elements in the complex of Southern Ocean ecosystems. 

This final report summarizes work conducted with the support of the 

National Aeronautics and Space Administration's Announcement of Opportunity 

for Thematic Mapper Research, under contract NAS 5-28755. Additional 

support came from the National Science Foundation's Division of Polar 

Programs grant DPP-85-07483. 

The following persons contributed to the research described in this report: 

William S. Benninghoff, David F. Parmalee, Kathy Wehnes, Zhenqui Ma, 

Zhiliang Zhu, Jerry Mullins, David G. Ainley, and Wayne Z. Trivelpiece. 

The conclusions drawn are, however, solely the responsibility of the 

authors. 
Table of Contents 

Acknowledgements ........................... ii 

List of Figures ........................... iv 

List of Tables ........................... V 

Introduction ............................ 1 

Objectives ........................... 2 

Technical Background ........................ 3 

Methods ........................... 7 

Data Analysis .......................... 10 

Derivation of Rookery Population Estimates ........... 10 

Developing A Regional and Continent-wide Inventory ....... 10 

Results ........................... 11 

Discussion ........................... 16 

Literature Cited .......................... 18 

Appendices: a i 

A. Bivariate scatter plots for laboratory, ground, and 

satellite measurements of terrain reflectance ........ 20 

8. Copy of paper published the Antarctic Journal of 

Draft copy of paper submitted for publication in 

TheAuk ........................... 42 

the United States (Volume XXI - No. 5) ............ 39 

C. 
List of Figures 

Figure 1. Spectral hemispherical reflectance, measured with 

a Beckman DK-2A spectroreflectometer, of four 

terrain materials ..................... 4 

Figure 2. Vertical aerial photograph showing the size and 

location of the north and south nesting sites 

for Adelie penguins on Cape Crozier ............ 8 

Figure 3. Bivariate scatter plots of brightness in TM bands 

Figure 4. Bivariate scatter plots of brightness in TM bands 

Figure 5. Comparison of a panchromatic aerial photograph from 

4 and 3, and 5 and 3, for six terrain materials ...... 12 

5 and 4, and 7 and 4, for six terrain materials ...... 13 

the SCAR archives with a computer classified image 

of the Adelie penguin rookery at Cape Crozier ....... 14 

Figure 6. Computer-classified gray-map of the Adelie 

penguin rookery at Cape Crozier .............. 15 

-iv- 
List of Tables 

Table 1. Brightness ratios for various materials from the 

Antarctic environment .................. 5 

Table 2. Approximate TM coverage schedule and solar 

elevation angles for ground targets at high 

latitudes during the period of proposed TM 

data acquisition ..................... 9 

-V- 
ESTIMATING POPULATION SIZE OF 

PYGOSCELID PENGUINS FROM TM DATA 

Charles E. Olson, Jr. 

Mathew R. Schwaller 

Paul A. Dahmer 

The University of Michigan 

School of Natural Resources 

Remote Sensing Laboratory 

Ann Arbor, MI 

EOSAT Corporation 

Now with SAIC McLean, VA 

Now with ERIM, Ann Arbor, MI 

INTRODUCTION 

The Southern Ocean ecosystem is one of the largest, most productive, and 

poorly understood natural sygems on earth. 

this ecosystem is, to a large extent, due to logistical difficulties of 

operating in this harsh and remote region. It is widely believed, however, 

that the isolation of the Southern Ocean ecosystem is being broken by 

commercial exploitation of Antarctica's renewable and non-renewable 

resources. The potentially harmful results of commercial activities led 

the 16 signatories of the Antarctic Treaty, plus a larger number of 

non-member nations, to express concern about Antarctica's future to United 

Nations Secretary General Javier Perez de Cueller. The United Nations is 

now preparing a "comprehensive, factual, and objective study on all aspects 

of Antarctica." 

Our lack of understanding of 

The unique observational capabilities of the Landsat Thematic Mapper (TM) 

can provide an important aid in Antarctic reconnaissance. We have focused 

our attention on the use of TM data for monitoring the dynamics of penguin 

populations in Antarctic and sub-Antarctic latitudes. 

As a class, penguins are one of the most important biological components of 

Southern Ocean ecosystems. Penguins account for the vast majority of 

terrestrial vertebrate biomass in the Antarctic, and a single species--the 

Adelie penguin (Pygoscelis ade1iae)--makes up approximately 90% of the 

Antarctic bird biomass (Croxall and Prince, 1979). To date, most studies 

have been confined to local surveys of the territorial and social behavior 

of these birds. There is, however, a growing interest in the study of the 

ecology and population dynamics of Antarctic seabirds on a regional basis. 

Interest in investigating penguins over a larger territory is motivated, in 

part, by the observation that penguin populations, and especially Adelie 

populations, have been increasing (Conroy, 1975; Croxall and Kirkwood, 

19,)). 

superba) is at least partially responsible for the rise in penguin numbers. 

Krill is the key species in the food web of the Southern Ocean; Euphausia 

It has been hypothesized that an increase in krill (Euphausia 

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superba 'is the main prey of numerous species of whales, seals, squid, fish, 

and penguins. It has been suggested that the active whaling industry has 

diverted feeding biomass from whales to penguins, supporting an increase in 

penguin numbers (Sladen, 1962; Emison, 1968). A krill fishery, althcugh 

still in its infancy, has begun to develop in the Southern Ocean. The 

apparent effects of the whaling industry on penguin populations and the 

strong interactions among all Southern Ocean species raise the possibiiity 

that commercial exploitation of krill will be at the expense of predators 

that feed in Antarctic and sub-Antarctic waters. Croxall and Prince (1979) 

have suggested that monitoring changes in the breeding xiumbers of 

krill-feeding seabirds, such as the Adelie penguin, may serve as an index 

of the distribution and availability of prey stocks. With the advent of a 

large scale krill fishery such an index may be particularly useful for 

setting realistic catch limits. 

In accepting these views the Scientific Committee on Antarctic Research 

(SCAR) endorsed a large scale study of "Biological Investigations of Marine 

Antarctic Systems and Stocks" (BIOMASS). A SCAR working group proposed 

that progrsms be established to monitor Southern Ocean species including 

whales, seals, and sea birds (SCAR, 1979), because changes in the 

population density of these species may serve as sensitive indicators of 

the vitality of the Southern Ocean ecosystem. 

Several of the Antarctic treaty nations, led by activities of the 

British Antarctic Survey, have been monitoring penguin populations in 

ground-based studies of rookeries on several areas bordering the Antarctic 

and sub-Antarctic waters. As a compliment to these conventional methods of 

measurement and reconnaissance, modern remote sensing techniques are 

expected to improve the power, scope, accuracy, and economy of data 

collection in the Antarctic. 

3 OBJECTIVES 

We began our study with four primary objectives: 

1. To determine the most suitable spectral regions for detecting and 

monitoring penguin rookeries by studying the reflectance 

characteristics of the birds and their backgrounds. 

2. To employ Thematic Mapper (TM) data as a means of detecting the 

size, location, and extent of Adelie penguin rookeries. 

3. To estimate penguin population size at a rookery based on its 

areal extent and available data on penguin colony density. 

4. To develop an inventory plan, based on TH data, for estimating 

the size of the total population of Adelie penguins. 

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TECHNICAL BACKGROUND 

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Modern remote sensing methods have not been extensively or systematically 

employed in Antarctic ornithology and ecology. At the start of this study, 

only one investigation had been conducted to evaluate the utility of 

satellite data for identifying penguin rookeries (Ott, 1982). -This study 

was based on data acquired with the Landsat-1 Multispectral Scanner (MSS) 

on February 16, 1973, a date after the end of the Austral summer breeding 

season when penguins are on the rookeries. No firm conclusions were 

reached regarding the value of satellite remote sensors for such work in 

the Antarctic. In the conclusions and recommendations Ott wrote: 

"Of the products generated, it is our impression that the false 

color composite is most useful. However, persons more experienced with the Antarctic might reach other conclusions. In 

addition, different conclusions might well have been reached if a 

more optimal LANDSAT acquisition date were available." 

"We recommend the LANDSAT-D data be special-ordered during the 

hovember-December time period. ... If Thematic Mapper data are 

available, the higher resolution- (approximately 30m) could be 

quite helpful." 

Prior to the ERIM study, all remote sensing investigations of penguin 

populations reported in the literature by Antarctic ecologists and 

ornithologists were based on aerial photographs (Bauer, 1964 IS 1-967; 

Stonehouse, 1969; Sladen and Leresche, 1970; Butler and Muller-Schwarze, 

1977). These large scale photographs proved successful because individual 

birds or nests could be detected and counted. 

techniques are best suited to relatively local surveys, whereas satellite 

techniques offer particular advantages for inventories of extensive areas. 

To be useful, satellite remote sensing systems must be capable of recording 

something closely correlated with penguin numbers, for the resolution of 

available satellite sensors is insufficient to permit direct detection and 

counting of the birds. The Thematic Mapper (TM) carried by Landsat-4 and -5 

appears to provide the needed capability. 

Spectral reflectance measurements of plumage from a single Adelie penguin, 

a sample of -three Adelie guano covered pebbles, and several other Antarctic 

--- materials (Figure 1) have been collected (Schwaller, et al., 1984). 

The reflectance of penguin plumage and guano are unlike reflectance from 

snow and rock, the two most common Antarctic terrestrial backgrounds. 

Experience has shown that objects with such differences in reflectance, at 

least at some wavelengths, can be differentiated from each other on the 

basis of remote sensor data. Relatively small reflectance differences can 

be amplified when data in two different spectral bands are ratioed. Ratios 

of the average reflectance of the materials in Figure 1, for the spectral 

bands of the Landsat TM are shown in Table 1. The TM Band 5 to TM Band 2 

ratio for penguin plumage is several times greater than the reflectance 

ratios for the other materials. Other band to band ratios can be used to 

separate guano covered pebbles from basalt and snow. Ratios for penguin 

plumage and guano covered pebbles are almost always higher than the 

corresponding ratios for their basalt or snow backgrounds. Thus, a scene 

element containing all plumage, all guano covered pebbles, or a mixture of 

the two, should be readily distinguishable from scene elements consisting 

of basalt or snow, or a combination of these background materials. 

Such aerial photographic 

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WAVELENGTH lrml 

Figure 1. Spectral hemispherical reflectance, measured with a 

Beckman DK-2A spectroreflectometer, of: 

1- Adelie penguin plumage (Schwaller et al., 1984) 

2- Adelie guano covered pebble 

3- guano free pebble from Adelie rookery 

4- new snow (Suits, 1978) 

Spectral bandwidths for the Landgat MSS, Landsat TM, 

and SPOT sensors are indicated by horizontal bars in 

the upper left. 

-4- 
Table 1. Brightness ratios for various materials from the Antarctic 

environment. See Figure 1 for the spectral reflectance data and bandwidths 

of the various satellite channels. 

Environmental Material 

Band Ratio Guano 

Penguin Covered Basalt 

Plumage Pebble Pebble New Snow 

Landsat 4 TM 

Band 5/Band 1 22.9 1.5 

Band 5/Band 2 22.9 1.2 

Band 5/Band 3 15.3 1.0 

Band 5/Band 4 5.1 0.9 

Band 4/Band 3 3.0 1.1 

Band 3/Band 2 1.5 1.2 

Band 4/Band 1 4.5 1.6 

Band 4/Band 2 4.5 1.3 

Band 3/Band 1 1.5 1.5 

Band 2/Band 1 1 .o 1.3 

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0.9 

1 .o 

0.9 

1.1 

1 .o 

1.1 

1 .o 

1 .o 

1 .o 

0.1* 

0.1* 

0.1 

0.9 

0.9* 

0.9* 

1 .o 

1 .o* 

1 .O* 

1 .o* 

Landsat MSS 

Band 7/Band 4 6.5 1.4 1 .o 0.8* 

Band 7/Band 5 4.9 1.1 1 .o 0.8 

Band 7/Band 6 3.1 1.1 1 .o 0.8 

Band 6/Band 4 2.1 1.1 1 .o 0.8* 

Band 6/Band 5 1.6 1.1 1 .o 1 .o 

Band 5/Band 4 1.3 1.2 1 .o 1 .o* 

SPOT 

Band 3/Band 1 4.1 1.4 1.0 G.9* 

Band 3/Band 2 

Band 2/Band 1 

3.1 1.1 1 .o 0.9 

1.3 1.2 1 .o 0.9* 

* Data below 0.6 pm extrapolate from Suits (1978). 

-5- 
In addition to their spectral characteristics, the size of Adelie rookeries 

makes them appealing targets for remote sensing inventory. Although the 

spectrophotometric characteristics and sheer size of penguin rookeries 

suggest that they can be detected in TM imagery, it is necessary to 

consider the potential problems of remote sensing in the Antarctic. 

sun angles in the Antarctic can produce difficulties. At low sun angles, 

effects of "haze" due to atmospheric scattering of sunlight become more 

severe, particularly at shorter wavelengths. This can make TM Band 1 

(0.45-0.52 um) unusable. 

radiation, particularly in TM Band 5 because of the significant optical 

density of the atmosphere in the wavelengths around 1.5 um, and because the 

solar flux is low at these wavelengths. There is also the question of the 

weather, which is notoriously cloudy along much of the Antarctic coast. 

Low 

Low sun angles also increase absorption of solar 

Assuming that the extent of the penguin rookeries can be discerned from TM 

data, this information could be used to conduct a census of the total 

Adelie population. Research has found that Adelie nests are spaced closely 

and regularly, with an average area per nest of 0.75 square meter (Penney, 

1968). This regular spacing suggests that a penguin census can be based on 

a ratio estimation method employing TM data. Ratio estimation takes 

advantage of an auxiliary variable x. (in this case the size of the 

rookery) to estimate the population total of a correlated variable of 

interest y (in this case penguin population). Ratio estimation has two 

advantages. One, the precision of the estimate is generally greater than 

with random sampling due to the correlation between x and y. Two, the 

ratio estimator is the best linear, unbiased estimator if the relation 

between the auxiliary variable x and the variable of interest y is a 

straight line through the origin, and if the variance of y about this line 

is proportional to x (Cochran, 1977, pp 158-159). We can safely assume 

that the relation begween x and y passes through the origin, since if the 

rookery extent is zero the population size is also zero. Furthermore, the 

regular spacing of nests within a rookery argues for an approximately 

linear relationship between population size and rookery extent. The 

functional relationship between the variance of y and x is unknown, but i i adjustments can be made in the estimator if the variance of y is not 

strictly proportional to x 

In addition to the statistical advantages of a ratio estimator, there are 

also practical advantages to using this method for a penguin census. It is 

relatively cheap and easy to measure rookery size with remote sensing. 

Information on rookery extent plus a knowledge of the ratio of penguin 

numbers to rookery size can be used to estimate population size. This same 

estimate ciuld, of course, be obtained by conventional means; however, 

directly counting birds in aerial or ground surveys becomes prohibitively 

expensive and increasingly unreliable as the scope of the census increases. 

Thus, estimating the size of the total penguin population with the help of 

TM data can yield more precise results than conventional methods, may do so 

more easily, quickly, and at less cost. 

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METHODS 

The experimental plan for this investigation was based on standard remote 

sensing techniques: data acquisition; data analysis, algorithm development 

and training from ground truth; and verification. 

Study Site 

The principal study site was the large Adelie rookery on Cape Crozier, on 

the eastern shore of Ross Island, an area which borders the Ross Sea at 

approximately 77'30s ' latitude and 169'15E' longitude. This is a well 

known and well studied rookery located about 100 kilometers from McMurdo 

Station, a major U.S. Antarctic research base. The aerial photograph in 

Figure 2 shows the extent of the rookery on Cape Crozier, covering from 2 

to 3 square kilometers. This rookery has an Austral summer population of 

up to 350,000 birds (Penny and Lowry, 1967; Leresch and Sladen, 1970). 

Additional work was also done at rookeries on Cape Bird and Cape Royds. 

A search of the Landsat-1, -2, and -3 data archives was conducted to 

determine the availability of imagery for five coastal locations with large 

penguin populations: Ross Island, Cape Hallett, Anvers Island, Geologie 

Archipelago, and Hope Bay. In the preceding 10 years, 25 scenes potential 

Landsat scenes were identified. To ensure independence, 13 samples from 

the set of 25 were eliminated so that-no scene was collected within 14 days 

of another. Of the 12 remaining samples, 3 had 10% or less cloud cover. 

This yielded an estimate that on a given trial there is a 75% chance (k13% 

error bound) that no suitable imagery will be obtained due to overcast 

conditions. If weyse the mean of 75%, assuming that samples are 

independent, the binomial distribution can be used to predict that there is 

an approximately 50% chance that no suitable scenes will be imaged after a 

series of three trials. 

(>go% probability) that one or more acceptable scenes will be imaged in a 

series of eight trials. 

We can azo predict that it is almost certain 

Fortunately, the convergence of the Landsat-5 orbit near the poles frees 

the data acquisition schedule from the strict constraints of the equatorial 

16-day repeat cycle of Landsat-4 oro-5. 

schedule for a ground station at 77 05'5 latitude, comparable to the 

schedule expected at Cape Crozier and Cape Hallett. 

in range of the TM scanner for 6 days of the 16 day cycle on the "day" 

orbit, 5 on the "night" orbit, and no coverage is obtainable for only 6 

days of the 16 day cycle. 

elevation at Cape Crozier at the time of satellite overpass for the Austral 

summer months. 

months of November to January for the "day" orbits, and 8' to 13' for the 

"night" orbits. 

was decided to collect TM data during "day" orbits only. 

Table 2 lists the coverage 

The ground station is 

Table 2 also lists the approximate solar 

Solar elevation is on the order of 23' to 28' during the 

Given the relatively low sun angle for "night" orbits, it 

Coverage of TM Path 53, Row 116 (Ross Island) was requested for the 

November 1985 to January 1986 Austral summer; the period coinciding with 

maximum rookery occupation (Penney, 1968). Plans for acquiring data for 

Cape Hallet (Path 63, Row 111) were cancelled when the 1985 price 1 crease 

for Landsat data caused a cut-back in data availability. 

-7- 
Figure 2. Vertical aerial photograph showing the size and location of the 

north and south nesting sites for Adelie penguins on Cape 

Crozier. The rookeries are readily distinguishable from snow, 

ice, water, and rock in this panchromatic image from the archives 

of the U.S. Geological Survey National Cartographic Information 

Center. 
Table 2. Approximate TM coverage schedule and solar elevation angles for 

ground targets at high latitudes during the period of proposed TM 

data acquisition. 

Sixteen Day Coverage Schedule for October 1 to 16 

Days Nights Misses 

1st 

3rd 

5th 

8th 

10th 

12th 

4th 

6th 

8th 

13th 

15th 

2nd 

7th 

9th 

11th 

14th 

16th 

- 

Landsat-5 may pass within range of the ground area located at 

77'05's on the "day" orbit, the "night" orbit, or a miss may 

occur if the ground area is not within the field-of-view of the 

TM scanner on a given day. 

coverage occurs approximately once every 48 hours. 

At this latitude, "day" or "night" 

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Mid-Month Solar Elevation Angles at Cape Crozier During the Austral Summer 

Solar 

Elevation Angle 

Solar 

Elevation Angle 

For Day Grbits 

October November* December* January* 

13' 23' 28' 23' 

For Night Orbits 

October November* December* January* 

8' 13' 8' 

* Months of maximum rookery occupation (Penney, 1968). 

February 

14' 

February 

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Data Analysis 

Image analysis was conducted on the Land Analysis System in the Laboratory 

for Terrestrial Physics at the NASA Goddard Space Flight Center. This work 

was based.on our analysis of spectral reflectance measurements of guano, 

snow and three types of volcanic rock materials (tuff, andesite, and 

basalt) common in the area around penguin rookeries on Ross Island. These 

data included both laboratory measurements made with a Beckman DK-2A 

spectrophotometer and field measurements made with a three-band radiometer 

and halon reflectance standard designed by C. J. Tucker (Tucker et 

al., 1981) at NASA Goddard. 

The reflectance measurements made with the Beckman DK-2A 

spectrophotometer included the spectral region from 0.38 to 

2.6um. 

the wavelengths corresponding to the 6 reflective channels of the 

Thematic Mapper. 

Spectral reflectance measurements were integrated over 

Ground level measurements made with the three band radiometer 

corresponded to TM bands 3,4, and 5. The measurements were made 

during January 1986 at Cape Crozier for four ground types: 

penguin colonies (n=61), exposed basalt (n=26), exposed tuffs 

(n=26), and snow, (n=30). 

Discriminant analysis, clustering, and graphical analysis were applied to 

the data to determine which channels contributed most to the separation of 

ground targets, and to assess the accuracy of separation. 

Derivation of Rookery Population Estimates 

Starting with the observation that there is a relatively constant packing 

density of penguin nests within colonies (Penney, 1968), we developed 

linear models which describe the relationship between colony area and 

Adelie nesting population. The models were then re-defined into 

statistical estimators which, given the total colony area within a rookery, 

allows one to predict the total number of nests, and to place an upper and 

lower limit on the estimate. 

Developing a Regional and Continent-Wide Inventory 

The long term objective is to develop a statistically sound design for a 

regional and continent-wide population survey of pygoscelid penguins in 

Antarctica. The number and cost of TM scenes needed to survey the entire 

Antarctic coastline is too large for a total practical survey based on TM 

data. 

multi-stage design that incorporates ground-based information, high 

resolution aerial photographic and/or satellite imagery, plus low 

resolution satellite imagery such as NOAA AVHRR-LAC data. The low 

resolution AVHRR data would be used to identify snow-free/ice-free coastal 

areas which have potential as rookery sites. Higher resolution data would 

then be used to determine if a rookery is there; and, if so, how large it 

is. 

We anticipate that a continent-wide survey will rely on a 

-10- 
RESULTS 

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Bivariate scatter plots based on the laboratory reflectance data, the field 

radiometer data, and the TM brightness values for the Ross Island subscene 

are shown in Appendix A. In each case, the brightness of different terrain 

materials is shown for two TM spectral bands. The scatter plots derived 

from the TM data for bands 5 and 3, and bands 4 and 3, are also shown in 

Figure 3. In both of these two plots, snow and ice are clearly separable 

from all other materials, but the rookery mixes with tuff. Scatter plots 

derived from the TM data for bands 7 and 4, and bands 7 and 5, are shown in 

Figure 4. 

separable from all other materials, and the rookery stands out more clearly 

than in either plot of Figure 2. In the plot of bands 7 and 5, the snow 

and ice cannot be separated from other materials, but the rookery is 

clearly distinguishable from all other materials. 

bands of the TM sensor provides information which helps distinguish between 

some of the terrain materials. Taken together, the TM spectral bands were 

found to be sufficient for identification of rookeries from their 

background materials. Data transformations, including two-band ratios, 

were not required. 

In the plot of bands 7 and 4, the snow and ice are clearly 

Each of the spectral 

Results of these image analyses are summarized graphically in Figure 5, 

where black and white aerial photography of the Cape Crozier penguin 

rookery are compared with a classified TM image. In bo$h cases the penguin 

rookeries are clearly evident, and the physical extent 'of the rookeries can 

be estimated from the TM data by counting pixels belonging to the rookery. 

The classified TM image was prepared by Earth Satellite Corporation using 

proprietory programs. Similar results were obtained at the University of 

Michigan using readily available programs and simple output devices 

(Figure 6). Preliminary results of our image analyses have been published 

in the Antarctic Journal of the U.S. (Appendix B). 

Examination of Figure 5 suggested a relatively simple first order linear 

model should give a good fit to data relating colony area and nesting 

population. A series of hypothesis tests found that a weighted linear 

statistical model (where weight was proportional to colony area) provided 

an excellent fit to the data relating colony area, X, and the 

number of nests per colony, Y. The model can be described as follows: 

A 

where w = l/xi i Yi = Xi + wiei 

2 Using this model, coefficients of determination (r ) of 0.90, 0.95, and 

0.88 were obtained for regression of colony area and population when data 

were collected over the Cape Royds rookery, the Cape Bird rookery, and a 

pool of data from both rookeries, respectively. The results of this 

research phase are summarized in a report prepared for publication 

(Appendix C) . 

It is anticipated that the continent-wide estimate of penguin populations 

will be a complex survey. Assuming a multi-stage design, a considerable 

amount of flexibility is permitted when choosing the number of samples at 

each stage. An optimum design is one in which the precision is maximized 

for a given level of cost or effort. 

necessary to estimate the cost and variance associated with each stage of 

the sample. Factors which need consideration include: the number of 

-1 1- 

To obtain the optimum design it is 
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SCAR ARCHIVE 

AERIAL PHOTOGRAPH 

LANDSAT THEMATIC MAPPER 

ZOMPOSITE OF BANDS 3,4 & 5 

1 ._. A. J 1 km 0 1 km 

I J 

1 km 

1 

1 km 0 

LEGEND 

C =CLOUD 

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ROOKERY 

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Figure 5. Comparison of a panchromatic aerial photograph from the 

SCAR archives with a computer classified image of the 

Adelie penguin rookery at Cape Crozier. The computer 

classified image is a composite of TM bands 3, 4, and 5, 

and was prepared by M. R. Schwaller at the NASA Goddard 

Space Flight Facility, Greenbelt, Maryland, from the data 

for Path 53, Row 116 (Ross Island) acquired 26 January 1985. 

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Figure 6. Computer classified gray-map of the Adelie penguin rookery 

at Cape Crozier prepared by Z. K. Ma at the University of 

Michigan using all seven channels of the TM data for Path 53, 

Row 116 (Ross Island) acquired 26 January 1985. 

-15- 
satellite images and the cost of locating rookeries on these images, the 

number of rookeries to sample for estimation of total rookery size, the 

number of rookeries to sample with ground and aerial photographic 

reconnaissance, which rookeries to sample, and the cost. All of these 

factors can be quantitatively estimated to obtain the optimum sampling 

design and to estimate precision for a given level of cost. We now believe 

a three year period. We do not believe it is appropriate to undertake a 

continent-wide survey without first testing the design concept on an area 

larger that a simple landsat scene. 

DISCUSS ION 

This study represents an important first step toward a continent-wide 

estimate of penguin populations. The results of this study indicate that 

TM data can be used to identify penguin rookeries due to the unique 

reflectance properties of guano. Furthermore, strong correlations exist 

between nesting populations and rookery area occupied by the birds. These 

correlations allow estimation of the number of nesting pairs in colonies. 

The success of remote sensing and biometric analyses lead us to believe 

that a continent-wide estimate of penguin populations is possible based on 

a timely sample employing ground-based and remote sensing techniques. 

It is interesting to note that differences in tone are apparect in the 

classified TM image (Figure 5). These differences may possibly be 

attributed to variations in nesting density within the rookery. If this 

association can be quantified, it could be developed into an excellent 

estimator of rookery population 

Gray-maps, like that in Figure 6, can be prepared without the sophisticated 

computer used to prepared the color composite in Figure 5. The software 

used to prepare Figure 6 is being adapted for stand-alone use on a personal 

computer comparable to an IBM-AT, and could be used to provide a meaningful 

image analysis capability in Antarctica. 

Several technical problems remain before a continent-wide population survey 

is feasible. 

1. Establishment of the relationship between penguin rookery density 

and radiometric response observed in satellite imagery. 

2. Development of multi-stage sampling methods which employ coarse 

resolution remote sensing data such as AVHRR-LAC. 

3. Solution of the logistic problems of ground-based and remote 

sensing data collection. 

that a timely and cost efficient estimate of pygoscelid penguin populations 

for the entire continent of Antarctica can be developed and implemented in 

Several important scientific questions, posed in the literature, await 

-16- 
accurate estimation of penguin populations on continent-wide and large 

regional scales. These questions include: 

1. Location of previously undiscovered rookeries that have been 

hypothesized based on observations of penguins at sea, especially 

along the coastline of Marie Byrd Land (Siple and Lindsey 1937; 

Ainley et al. 1984). 

2. Use of penguin population estimates as an index of the Southern 

Ocean ecosystem vitality (Croxall and Prince 1979). 

Test of hypotheses that size and distribution of neighboringrookeries are related to competition for food resources (Firness 

and Birkhead 1984). 

.._ :.. 

3. 

4. Test of hypothesis that species composition of penguin rookeries 

is a function of physical factors, especially pack ice 

distribution (Ainley et al. 1983; Trivelpiece et al. in press). 

In summary, the results of this research can be integrated into survey 

methods for estimating penguin populations on a continent-wide basis, 

Using the techniques that we envision, meridional as well as total penguin 

populations estimates may also be possible. In addition, satellite remote 

sensing along the coastline njay well locate previously undiscovered penguin 

nesting sites, or locate rookeries which have been assumed to exist for 

over half a century--but which have never been located. 

being developed for submittal to NASA and NSF to support the research 

necessary to conduct a continent-wide survey. The results of a 

continent-wide survey of penguin populations will contribute to an 

understanding of the influence of the physical environment on rookery 

choice and breeding success, the patterns of penguin migration, and 

population fluctuation. 

Proposals are 

-1 7- 
Ainle 

LITERATURE CITED 

, D. G., R. E. LeResche, and W. L. Sladen. 1983. Br eding Biology 

of the Adelie Penguin. University of California Press. Berkeley. 

Ainley, D. G., E. F. O'Connor, R. J. Boekelheide. 1984. The marine 

ecology of birds in the Ross Sea, Antarctica. Ornithology Monograph 

No. 32. American Ornithological Union, Washington, D.C. 97 pp. 

Bauer, A. 1964. Utilisation de la photographie verticale a l'etude 

ornithologique des Iles Australes. Terres Australes et Antarctique 

Franscaise. 25:34-38. 

Bauer, A. 1967. Denombrement des manchotieres de l'brchipel des Crozet et 

des Iles Kerguelen a l'aide de photographie aeriennes verticales. 

Terres Australes et Antarctique Franscaise. 41:3-21. 

Butler, R.G. and D. Muller-Schwarze. 1977. Penguin census by aerial 

photographic analysis at Cape Crozier, Ross Island. Antarctic Journal 

of the United States. 12:25-27. 

Cochran, W.G. 1977. Sampling Techniques. 3rd edition. John Wiley and 

Sons. NY. i 

Conroy, J.W.H. 1975. Recent increases in penguin populations in 

Antarctica and the Subantarctic. In B. Stonehouse, ed. The Biology 

of Penguins. University Park Press, Baltimore. 

Croxall, J.P. and E.D. Kirdwood. 1979. The Breeding Distribution of 

Penguins on the Antarctic Peninsula and Islands of the Scotia Seal. 

British Antarctic Survey. Cambridge. 

Croxall, J. D. and P. A. Prince. 1979. Antarctic seabird and seal 

monitoring studies. Polar Record. 19:573-595. 

Emison, W.B. 1968. Feeding preferences of the Adelie penguin at Cape 

Crozier, Ross Island. 3 O.L. Austin, Jr., ed. Antarctic Bird 

Studies. Antarctic Research Series. Volume 12. American Geophysical 

Union. Washington, D.C. 

Furness, R. W. and T. R. Birkhead. 1984. Seabird colony distributions 

suggest competition for food supplies during the breeding season. 

Nature. 311:655-656. 

LeResche, R.E., and W.J.L. Sladen. 1970. Establishment of pair and 

breeding s'ite bonds by young known-aged Adelie penguins Pygoscelis 

adeliae. Animal Behavior. 18:517-526. 

Mougin, J. L. and J. Prevost. 1980. Evolution annuelle des effectifs et 

des biomasses des oiseaux antarctique. 

d'Ecologie. 34:lOl-133. 

La Terre et la Vie Revue 

-18- 
-- 

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I 

Ott, J. S. 1982. Penguin monitoring with Landsat. Unpublished report 

RT-JSO-2503 by the Environmental Research Institute of Michigan, Ann 

Arbor. 

Penney, R. L. 1968. territorial and social behavior of the Adelie 

penguin. In Antarctic Bird Studies, 0. L. Austin, ed., Antarctic 

Research Series, vol. 12. Washington, D. C. : America1 Geophysical 

Union. 

Penney, R.L. and G. Lowry. 1967. Leopard seal predation in Adelie 

Penquins. Ecology. 48:879-882. 

SCAR. 1979. Fifteenth Meeting of SCAR. Charmonix, 16-26 May 1978. 

Appendix A. Working group on Biology. Polar Record. 19:304-312. 

Schwaller, M.R., W.S. Benninghoff, and C.E. Olson, Jr. 1984. Prospects 

for satellite remote sensing of Adelie penguin rookeries. 

International Journal of Remote Sensing. 5:849-853. 

Siple, P. A. and A. A. Lindsey. 1937. Ornithology of the Second Byrd 

Antarctic Expedition. &. 54:147-149. 

Sladen, W.J.L. 19.62. The distribution of the Adelie and Chinstrap 

penguines. & Biologie Antarctique. S.C.A.R. Paris 

Sladen, W.J.L. and R.E. Leresche. 1970. New and developing techniques in 

Antarctic ornithology. M.W. Holdgate, ed. Antartic Ecology. 

Volume 1. Academic Press. New York. 

Stonehouse, B. 1969. Air census of two colonies of Adelie penguines -- 

(Pygoscelis adeliae) in Ross Dependency, Antarctica. Polar Record. 

14:471-475. 

Stonehouse, B. 1985. Birds and Mannals--Penguins. In Key 

Environments--Antarctia, W. N. Bonner and D. W. H. Walton, eds., 

chapter 5d. New York: Pergamon Press. 

Suits, G.H. 1978. Natural sources. In W.L. Wolfe and G.J. Zissis, eds. 

The Infrared Handbook. 

Michigan. ,Ann Arbor. 

The Environmental Research Institute of 

Tucker, C. J., W. H. Jones, W. A. Kley, and G. J. Sundstrom. 1981. A 

three-band hana-held radiometer for field use. Science. 211:281-283. 

Wilson, G. J. and R. H. Taylor, 1984. Distribution and abundance of 

penguins in the Ross Sea sector of Antarctica. New Zealand Antarctic 

Record 6 : 1-7. 

-19- 
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APPENDIX A. BIVARIATE SCATTER PLOTS FOR LABORATORY, GROUND, AND 

SATELLITE MEASUREMENTS OF TERRAIN REFLECTANCE 

Laboratory Reflectance Data from a Beckman DK-2A 

Percent Reflectance and 95 percent confidence 

Percent Reflectance and 95 percent confidence 

Percent Reflectance and 95 percent confidence 

ellipses for four materials - TM4 over TM3 . . . . 21 

ellipses for four materials - TMS over TM3 . . . . 22 

ellipses for four materials - TM5 over TM4 . . . . 23 

Ground Reflectance Data from a Tucker 3-band Radiometer 

95 percent confidence ellipses for four materials 

95 percent confidence ellipses for four materials. 

95 percent confidence ellipses for four materials 

measured at Cape Crozier - TM4 over TM3 .... 24 

measured at Cape Crozier - TM5 over TM3 .... 25 

measured at Cape Crozier - TM5 over TM4 .... 26 

TM Brightiess (DN) Values on 26 January 1985 

TM2 over TM1 and TM3 over TM1 . . . . . . . . . . . 27 

TM4 over TM1 and TM5 over TM1 . . . . . . . . . . . 28 

TM6 over TM1 and TM7 over TM1 . . . . . . . . . . . 29 

TM3 over TM2 and TM4 over TM2 . . . . . . . . . . . 30 

TM5 over TM2 and TM6 over TM2 . . . . . . . . . . . 31 

TM7 over TM2 . . . . . . . . . . . 32 

TM4 over TM3 and TM5 over TM3 . . . . . . . . . . . 33 

TM6 over TM3 and TM7 over TM3 . . . . . . . . . . . 34 

TM5 over TM4 and TM6 over TM4 . . . . . . . . . . . 35 

TM7 over TM4 . . . . . . . . . . . 36 

TM6 over TM5 and TM7 over TM5 . . . . . . . . . . . 37 

TM7 over TM6 . . . . . . . . . . . 38 

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mmm 

aa~ e c am 

c +I- K ~KKK~ +K rmna~ 

-0 $0 

cc e :? 

nu cca~a KC 

c e aa ~aa-e + mam +I- , 

a cccccvl t 

+ ccec c 'P dm 

c cc c ulul I 

c cc cc v)ccul I 

c ec c ulvlvl +- 10 

c cccc ululvl I 

l- cc ululvl3I 

2 cvlcul~+m Ire+- I & 

me- 0 v) m -- +LII 

IC N 

0 

-38- 
APPENDIX C. DRAFT COPY OF PAPER SUBMITTED FOR PUBLICATION IN 

THE AUK 

"Ratio Estimation of Occupied Nests on Adelie 

Penguin Rookeries" 

Mathew R. Schwaller SAIC 

Paul A. Dahmer ERIM 

Charles E. Olson, Jr. University of Michigan 

a 

#