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IDENTIFICATION

OF TREE SPECIES

ON LARGE-SCALE

PANCHROMATIC

ANO COLOR AERIAL

PHOTOGRAPHS

U.S. DEPARTMENT OF AGRICULTURE FOREST SERVICE AGRICULTURE HANDBOOK NO. 261
IDENTIFICATION OF TREE

SPECIES ON LARGE-SCALE

PANCHROMATIC AND COLOR

AERIAL PHOTOGRAPHS

By R. C. Heller, G. E. Doverspike, and R. C. Aldrich, Research Foresters,

Forest Insect Laboratory, Forest Service, U.S. Department of Agriculture, Beltsville, Md.

U.S. DEPARTMENT OF AGRICULTURE Agriculture Handbook No. 261

FOREST SERVICE July 1964
Contents

Page

Study area and species 1

Methods of obtaining data 1

Collection of ground data 1

Collection of air data 2

Ofñce procedures and photo interpretation 2

Results 4

Discussion and conclusions 12

Literature cited 15

Appendix 16

For sale by the Superintendent of Documents, U.S. Oovernment Printing Office, Washington, D.C., 20402

Price 30 cents
IDENTIFICATION OF TREE SPECIES ON LARGESCALE PANCHROMATIC AND COLOR

AERIAL PHOTOGRAPHS

This report, which describes results of research

conducted near Ely, Minn., in July 1960, indicates

the best film and scale combination for identifying

tree species. These results should be applicable

not only to inventories of timber but also to other

projects—such as those to assess damage to

forests by destructive enemies, to appraise forest

wildlife habitat, and to expedite forest administration.

Forest photo interpreters have recognized for

some time their inability to identify nnages of

individual tree species on small-scale aerial photographs (1:15840 or smaller). With experience

and knowledge obtained by photo scrutiny,

interpreters can now separate forest stands into

broad species classes, but they can seldom determine the species of individual tree images at these

scales.

Why must foresters identify trees? Those of us

concerned with the national timber situation must

know what is happening in the woods. How are

the trees growing? What is the condition of the

forest after harvesting? Is it regenerating? Are

there destructive forces at work, such as fire,

insects, or disease? And finally, how much and

what kind of timber is available? Data are

gathered in many ways to answer these important

questions—most of it by expensive ground surveys.

Because there are 490 million acres of commercial

forest land in the United States (Oy and much of

it is inaccessible, sampling techniques are used to

make these ground surveys more rapid and less

costly. Additional savings in time and money

can be expected if more of this expensive ground

sampling can be replaced by photo sampling,

without sacrificing accuracy.

Study Area and Species

In northern Minnesota the terrain is rolling and

interspersed with lakes, and it was previously

glaciated. Forests cover about 85 percent of the

land area. A boreal area was chosen, because

fewer species needed to be compared.

Fourteen important tree species were selected

on 29 separate locations. Nineteen replicates

were taken of eight of the most important species,

and fewer replicates of the other six species. This

fact was not revealed to the photo interpreters;

thus, equal consideration was given to all 14

species. All test trees were selected so the

physiographic features would not help the interpreter identify individual trees.

The species involved in the test were:

1. Abies balsamea (L.) Mill balsam fir

2. Picea glauca (Moench) Voss white spruce

3. P. mañana (Mill.) B.S.P black spruce

4. Pinus strobus L eastern white pine

5. Thuja occidentalis L northern white-cedar

6. Betula papyrifera Marsh white birch

7. Populus tremuloides Michx trembling aspen

8. Acer rubrum h red maple

9. Pinus resinosa Ait red pine

10. P. banksiana hamb jack pine

11. Populus balsamifera L balsam poplar

12. P. grandidentata Michx largetooth aspen

13. Sorbus americana Marsh mountain ash

14. Larix laricina (Du Roi) K. tamarack

Koch.

Methods of Obtaining Data

Collection of Ground Data

Trees were identified in the field on large-scale

(1:1000) black and white prints made from color

transparencies.^ To prevent possible bias, the

ground identifications were made by a forester

who did not take the interpretation test.

^ Italic numbers in parentheses refer to Literature Cited,

p. 15.

2 Since this study, a portable, battery-powered light

A detailed description was made of each tree

selected. This included species, diameter at

breast height, height, crown class, site class, and

other associated features. Only dominant, codominant, and intermediate crown class trees

were included since overtopped trees are not

visible on air photographs.

table was developed to directly locate objects on color

transparencies in the field. This device has been used in

several other studies with great success.
Collection of Air Data

A Hulcher 70-inin. camera ^ with a 150-min.

(5.91-iiu'h) focal leii^ilh lens was used. Details

about this camera and the modifications needed

to adapt it for aerial photo^Taphy were published

in 1959 (1).

The films used were Super Anscochrome (General Aniline and Film Corp.), with an ASA rating

of 125 for color; and Plus X Aerographic (Eastman

Kodak), with an ASA rating of 80 for the black

and white photographs.

Photographie scales were approximately 1:3960,

l:15S4/and 1:1188 (ñ^:. 3). These scales correspond to units of area measurement commonly

used by foresters in the Ignited States.

White panels were placed on the ground to

proyide identification of each of the 29 locations

on the photos while the pictures were being taken.

All film was deyeloped locally so that reflights

could be made if necessary. Glossy contact

prints with as nearly equal contrast as possible

were made from the panchromatic film.

Office Procedures and Photo

Interpretation

Cellulose acetate oyerlays were prepared; these

showed the location and number of each tree

located preyiously in the forest on each film and

scale combination (fig. 1).

An effort was made to determine whether

morphological features, such as crown apexes

and crown margins, which may be associated with

tree form and growth, would help increase interpreter accuracy. Botanical terminology was used

when possible, and drawings were made to help

the interpreter select the species (fig. 2).

Crown descriptions used by photo interpreters

in species identification test

3 The identification and description of commercial

products in this pubhcation are solely for information

purposes. Endorsement of any commercial product is

not intended and must not be inferred. FIGURE 2.—Interpretation aid for describing tree crowns.

FIGURE 1.—Method of locating trees used in species identification test (Scale 1: 1584, Plus X

film). Each number on the translucent overlay indicates a tree image to be identified

by photo interpreter.
FIGURE 3.—Photographic coverage of one study plot copied from Super Anscochrome film. From top to bottom, the scales are 1:3960, 1:1584, and 1:1188, respectively; the rectangle outlines the identical area of

coverage at each larger scale. The arrow with letters Ps points to a Pinus strobus referred to later in the

paper. A lens stereoscope placed over any two adjoining pictures will permit the reader to see the images

in 3 dimension.
The foliage density was classified as thin (less

than 25 percent), medium (26 to 75 percent),

and dense (more than 75 percent).

An entirely new set of terms was devised to

relate the foliage arrangement of the species to the

shape of the images on the large-scale aerial

photographs. These foliage descriptions and

drawings are shown in figure 4.

Five experienced photo interpreters examined

sample trees to define these foliage and branching

characteristics and to write specifications as to

how each species looked on aerial photographs.

This review of sample trees was used during the

training of the four experienced photo interpreters

and the one recent graduate from a forestry school

who were used in the test.

A Munsell gray scale was used on the panchromatic prints to correlate tone with species.

An innovation in the interpretation of color

film was the attempt to relate color represented

on the transparencies with Munsell standard

color chips (5, 6). These standards represent

spaced divisions of the three attributes of color:

Hue, value, and chroma. According to the

Munsell notation, the hue indicates a coloras

relation to red, yellow, green, blue, and purple;

the value its lightness; and the chroma its strength.

The color chips were remounted on special cards

with prepunched holes to facilitate color matching

(fig. 5). This type of mounting has previously

been used for soil sampling. The color matching

was done to see if the eye can associate tree

species with any one or all of the attributes of

color.

Another interpretation test was made of the

same tree images on film exposed in July 1962.

Instead of using the Munsell charts as before, they

were copied onto 35-mm. color film. The roll of

film was then inserted into a specially built

reflecting device (fig. 6), permitting the photo

interpreter to select the color chip that most

nearly matched the tree image being inspected.

This comparator device enabled the interpreter

to compare transparencies of the Munsell chart

and the tree image while viewing them stereoscopicaUy with the same kind of light source. It

also provided more uniform lighting than was

possible when reflected light was used on the

Munsell charts.

The panchromatic photographs were examined

with a 2.25-power stereoscope under reflected

light, starting with the smallest scale and proceeding to the largest.

The color transparencies were inspected with

a 2.25-power stereoscope mounted on a specially

built light table (fig. 7).

Uniform lighting and interpretation equipment

were used by all interpreters. Two interpreters

recorded their data (10 classes of information

for each tree) on tape recorders and later transferred it to the tally forms. This procedure was

much more eflicient since it was faster and less

tiring than immediately recording the interpretations on the tally forms.

All interpretation data were coded and put

on specially designed forms before being transferred

to IBM punchcards for tabulation and analysis.

Results

The IBM cards were sorted and tabulated by

correct and incorrect interpretations for each

species and interpreter. The percentages of the

correct observations were used as a basis for

subsequent analysis of variance after converting

percentages to angles (arc sine transformation,

Snedecor (8)). The analysis, based on photo

interpretation of images of eight species replicated

19 times, showed the following:

1. Interpreters.—No statistically significant

difference in accuracy was detected between

observations made by any photo interpreters of

color film. Their mean values and mean differences are shown in table 1; the difference in scale

means required for significance at p=0.05 is

3.05, as computed by Tukey^s range test (8).

However, the observations of the five interpreters

of panchromatic film were significantly different.

One man interpreted significantly better than the

two least accurate interpreters.

2. Film.—Interpretations of color transparencies were significantly more accurate than

those of black and white prints.

TABLE 1.—Mean photo interpretation accuracies

made by five photo interpreters on color film ^

Difference among interpreter means

Interpreter

X

A

X-54.43

C

X-54.70

B

x-55.18

D

x-55.91

F

D

B

57.14

55.91

55. 18

54.70

54.43

2. 71

1.48

.75

.27

2.44

1.21

.48

1.96

.73

1.23

c

A

1 Values shown are angles not transformed to percentages; a difference of 3.05 between interpreter means is

required for significance at the 0.05 probability level.
Conifers

Code No.

I. Light tip to center of

bole with fine texture

2. Layered branches

3. Wheel spokes

4. Columnar branches

5. Layered triangularshaped branches

6. Small clumps

7. Small light spots

in crown

8. Small starlike top

Hardwoods

12.

16.

Dark spot in center

of small clumps

^ '^

ste

>C#

Code No.

Small light spots

in crown

2. Small clumps

3. Small clumps with occasional

long columnar branches

( in young trees )

4. Limbs show

5. Large masses of foliage

divides crown (large older trees)

7. Fine texture

9. Fine columnar branches

Fine texture with

scraggly long branches

FIGURE 4.—Foliages characteristics most useful in separating 14 boreal tree species.

go
FIGURE 5.—Munsell color chart (10YR) used to compare color chip with tree image on a color transparency.
FIGURE 6.—Comparator device permits photo interpreter to select a matching color chip

while viewing tree images in stereo.

3. Photographic scale.—Interpretation was poorer

with the smallest scale than with the two larger

scales (fig. 8). Differences in interpretation were

highly significant among all scales on panchromatic

film. For the color transparencies, the two larger

scales were almost equally accurate, and both

were significantly better than the 1:3960 scale at

the 0.01 level (table 2).

4. Tree species.—Interpretation differences

among the eight tree species were highly significant. Obviously, the morphological and color

characteristics differ enough among tree species to

make some species easier to recognize than others.

Accuracy in interpreting color film was consistently

higher for each tree species than accuracy in interpreting panchromatic film (fig. 9). The black and

white spruces could not be separated accurately

even on color film.

TABLE 2.—Difference in accuracies attributable to

scale on colorfilm—average office interpreters '

Scale Scale_

mean x

Differences between

scale means

(1:3960)

X-47.04

(1:1584)

X-58.44

1:1188 60.95

58.44

47.04

13.91

2 (2. 74)

11.40

2.51

1:1584

(2. 74)

1:3960

' Computed by Tukey's range test (Snedecor) ; values

shown are angles and not percentages.

2 Values in parentheses show difference required for

significance at p = 0.05.
F-504452

FIGURE 7.—70-mm. transparency viewer with interpreter comparing a Munsell chart with a selected tree image. Note

tape recorder to facilitate recording data.

Three species will be discussed in detail (fig. 10).

Pinus strobus, which ranked first in accuracy of

recognition, showed little change between the two

larger scales. Betula papyrifera, which ranked

last, showed little improvement in accuracy with

increased scale. Recognition of Thuja occidentalis

was greatly improved with the increase in scale.

Photo images of some species may be harder to

recognize than others because of differences in

their morphological features and color characteristics, as in the three sample species.

1. Pinus strobus was accurately identified by

all interpreters. They consistently recognized its

characteristic foliage arrangement, e.g., a pattern

of massive triangular branches that radiate like

the spokes of a wheel. Furthermore, this species

has a greener hue than any of the other pines,

making correct interpretations easier. A Pinus,

strobus is illustrated in figure 3, p. 3; the arrow

points to a typical specimen.

2. Betula papyrifera was identified correctly by

its fine foliage texture when the tree was full

crowned and vigorous, but when the tree was

decadent and had thin foliage, its image was

generally confused with that of Populus tremuloides.

Both of these species have white bark that shows

through the foliage on older specimens, and this

similarity confused the photo interpreters. White

birch had a consistently yellower hue (lOY) and

a lower value (6.4) than any other hardwood

species. Young trees had stronger chroma than

old trees (fig. 11, A and 11, B).

3. Thuja occidentalis was recognized by sinnuate

crown margins, pointed apexes, light spots in the

foliage, and image color on the large scales. The

interpreters consistently designated this species as

8
100

80

60

>» 40

< 20

-> color

^ ^ ^^^^^^^

pan

^^

i:3960 .1584 1.1188

Photo scale

FIGURE 8.—Note improvement in accuracy obtained with

all scales on color film. Graph shows the average interpretation of five observers for all species.

100

80

« 60

o 40

20

Thujo occi

Betula pap ir\fer

i:3960 i:i584 i:il88

Photo scale

FIGURE 10.—How scale affects the photo interpretation

accuracy of three particular species.

Species ranked in order of interpretation accuracy —in percent

Panchromatic

Pinus

strobus

Thuja

occidentalis

Pinus

resinosa

Pinus

banksiana

Picea

spp.

Abies

balsamifero

Acer

rubrum

Populus

tremuloides

Betula

papyrifera

95 8! 80 80 77 73 70 59 44

Super Anscochrome

Pinus

strobus

Pinus

banksiana

Picea

spp.

Pinus

resinosa

Thuja

occidentalis

Abies

balsamifero

Acer

rubrum

Populus

tremuloides

Betula

papyrifera

97 96 88 88 86 84 73 64 56

I / Average of 5 interpreters — scale 11188

FIGURE 9.—Note better accuracies for each tree species on color film as compared with panchromatic film.
FIGURE 11.—Scale 1:1584, Super Anscochrome. Betula papyrifera (Bp) has fine texture and strong chroma

when young and vigorous (A), but the foliage tends toward large clumps in older specimens (B). Thuja

occidenialis (To) in C can be separated from other conifers by the light yellow spots in the foliage and the

small starlike crown apexes. Populus tremuloides (Pt) also in C has large masses of foliage and is the greenest in hue of all hardwoods.

10
FIGURE 12.—Scale 1:1584, Super Anscochromo. .1, Pinus hanksiana (Pb), jack pine; B, P. resinosa (Pr),

red pine; C, Acer ruhrum {Ar), red ma])le; IHcea glaciia (Pg), white spruce; and /lb¡>s halsamifera {Ah), balsam

fir. Note also many dead and dying balsam fir (.1. halsamifera) damaged by the spruce budworm (Choristoneura fumiferana), Clem., which appear light gray to pink.

11
having the yellowest hue of any conifer (8.5 Y).

None of these four characteristics were easily

recognized on the small scale (fig. 11, C).

The other species that had high interpretation

accuracies also had distinguishing foliage characteristics. For example, Pinus banksiana is recognized by its ragged branches (fig. 12, A). P,

resinosa has foliage in small clumps with a dark

spot in the center of each clump (fig. 12, B), and

older trees have broadly rounded crowns. Acer

rubrum has characteristically shaped columnar

branches and the strongest chroma of any species

studied (fig. 12, (7). Picea glauca and Abies

balsamijera are indicated in figure 12, Chj arrows.

Consistency of results is important to photo

interpreters. Therefore, three interpreters examined the same trees described in this paper on

Super Anscochrome film exposed in the summer

of 1962 at a scale of 1:1584 (fig. 13). Because of

better exposure of the film, two of the interpreters

obtained better species recognition than in 1960.

The third interpreter's accuracies were of the

same order as those found in the first interpretation. It is interesting and important to realize

that the same or better accuracies are possible in

using this photo interpretation technique with

the two independent inspections.

From the tabulations made from the punchcards, we learned which morphological and color

features contributed most to the correct identification of tree species. These are summarized

in the appendix. Each feature is given a weight,

so theoretically, if an interpreter identifies the

correct features of an image, he may use the total

of these weights to help him identify the species.

For example, if a tree image is a conifer (weight

0), has an acuminate crown apex (1), an entire

crown margin (1), a light tip to the center of the

trunk (1), a hue of lOGY (green yellow) (3), a

value of 8 (4), and a chroma of 4 (4), the image

should key out to a balsam fir {Abies balsamijera),

which averages a total weight of 14. When using

large-scale color film, interpreters were able to

separate conifers from hardwoods with almost

100-percent accuracy. The appendix table can

also be used as a training guide for photo interpreters who are unfamiliar with the timber types

and who should learn what crown, foliage, and

color characteristics are most commonly associated

with each species.

Pinus

strobus

Picea

spp.

Abies

balsam îfero

Pinus

banksiana

Pinus

resinosa

Thuja

occidentalis

Populus

tremuloldes

Acer

rubrum

Betula

papyrifera

All

spp.

100 97 97 97 97 90 90 74 67 90

FIGURE 13.—Average photo interpretation accuracies (in percent) obtained by two interpreters in 1962 test. Super

Anscochrome 70-mm. film was used (Scale 1:1584).

Discussion and Conclusions

Color film is superior to panchromatic film for

use in identifying individual tree species. Why?

First, people are accustomed to seeing and

identifying objects not only by shape and form

but also by color. A ripe tomato is picked from

the vine by its color rather than its shape, and

cotton can be graded by the lightness and yellowness of the fiber (7). A forester trained to

recognize trees by morphological features also

associates a color with that tree. When he is

trained to recognize the tree on aerial color photographs, he has one more factor on which to base

his determination. Thus, it requires more training for an interpreter to be able to recognize

objects by tones of gray than by the normal colors

with which he associates the object. In panchromatic interpretation he must learn to relate the

gray tone of the image to color, and by associating its form and texture, he tries to identify the

object.

Evans (4) reports that the eye can separate 200

tones of gray which are seen by the rods (brightness-sensitive nerves), whereas the cones (color

sensitive nerves) can distinguish 20,000 hues and

chromas. This 100:1 ratio may help explain why

the results from the color film were better than

those from the black and white prints.

At Nickerson's^ suggestion, the test data were

plotted on a chart representing hue, value, and

chroma (7) (fig. 14). Use of this chart indicated

that value or degree of lightness helped the photo

4 D. Nickerson, color technologist, Agr. Marketing Serv.,

U.S. Dept. Agr., gave considerable advice and assistance

in evaluating the data. The authors express their

appreciation.

12
Gray scale (pan.)

8 8

Value and chroma (color)

(A)

Tree species

Ab-Abies balsamifera

Pg "-Picea glauca

Pm-Picea Mariano

Ps - Pinus strobus

To - Thuja occidentolis

Bp — Betula popyrifera

Pt — Populus tremuloides

Ar " Acer rubrum

Pr - Pinus resinosa

Pb - Pinus banksiona

^Ar

hPg

+ Ab

Ps To

"% ^'•"

>

Pg Pm

J.P8

» Pt ^

4.Pr

4-Ar

+.Bp

4 6 7

Chroma (B)

Hue and chronna (color)

Hue ^_

5Gy

no insect domage

FIGURE 14.—Ten tree species depicted by by Munsell Color Notation. Graph shows gray-scale values for tree species on

panchromatic prints (A) and two-dimensional plotting for value and chroma on color film (B) and hue and chroma

on color film (C).

13
interpreter very little in separating tree species.

On panchromatic prints, the values (or tones)

were obtained by comparing a Munsell gray scale

with images of each species. (Value on panchromatic prints can be represented in only one dimension, along the ordinate). For example, white

birch had the lowest value rating (5.5 on panchromatic film and 6.4 on color) of any species and

was the only species where value was of any help

in separating it from a species similar in appearance. This was true on both color and black and

white film. Most other species had such a narrow

and overlapping range of values that no discrimination was possible. Gray-scale values and color

values were comparable although somewhat lower

for species on the panchromatic prints; this may

be caused simply by differences in darkroom procedures (table 3).

TABLE 3.—Comparison of the value scales for

panchromatic and color film jor 10 tree species,

1:1584 scale

Species

Betula papyrifera- _

Pinus banksiana

P. resinosa

Populus tremuloides

Pinus strohus

Thuja occidentalism.

Picea mariana

Abies balsamifera. _

Picea glauca

Acer rubrum

Panchromatic film

5.5

5.5

6.3

6. 4

6.9

6.9

6. 9

7. 1

7.4

7.6

Color film

6. 4

6. 7

7. 1

7.4

7.5

7. 7

7.7

7.6

7. 7

7.6

Value and chroma data derived from the color

transparencies were plotted as they would be on a

Munsell chart. While the differences in value

among species are still small on color film, by

adding another variable—chroma—greater separation between species can be seen (fig. 14, B).

Perhaps the greatest contribution to species

identification that color film makes is the huechroma combination. Interestingly, before taking the test, most of the interpreters had a preconceived notion that tree images would appear

green or blue green except for a few green yellows.

Their data, however, showed that most of the

species were tallied as yellow to green yellow and

that only two approached green.

According to the Munsell notation, hue or color

can be represented by 100 equally spaced increments of a hue circuit beginning with 1 red and

ending with 10 red purple. The 10 major hues are:

R* red BG: blue green

YR: yellow red B:

Y: yellow PB:

GY: green yellow P:

G: green RP:

blue

purple blue

purple

red purple

There is a wide spread in hue and chroma among

the conifers; pines have more chroma than fir and

spruces, and white pine averages three hues

greener than red or jack pine. Of the hardwoods,

red maple was consistently recorded with the

strongest chroma, while trembling aspen was

greener than red maple or white birch. These

distinctions can be seen in fig. 14, C.

Because the 1960 color pictures were overexposed, the comparison of the color attributes was

made with the 1962 pictures. Chroma seems to be

most affected by camera exposure; overexposure

tends to wash out the strength of the color, thus

reducing the effectiveness of one color attribute.

The frequency of hues observed by photo interpreters for each species exhibited a definite central

tendency such as that found in a normal curve of

error. However, the upland spruces and balsam

fir had a rectangular distribution of hue (7.5YR to

2.5G) caused by spruce budworm feeding damage

to foilage of these species. Various degrees of

budworm feeding caused foliage to change from

green through yellow to red brown (YR). Thus,

the hues can be correlated with the degree of

damage that occurred. This relationship is particularly interesting to forest entomologists. In

the absence of defoliation, the normal hues for

these species were found to be greener than when

all degrees of defoliation were included (see circles

in fig. 14, C),

The slight range of hues for each species may be

attributed to two factors: (1) A normal variation

in hue within tree species and (2) an actual

physiological difference in the receptivity of

human eyes. This diversity of receptivity is particularly important; for example, about 8 percent

of males do not have trichromatic vision. However, color blindness tests {2, 3) are available and

should be taken to avoid unwanted variation

between interpreters, if much color photo interpretation work is contemplated.

On the basis of this test, accurate identification

of individual tree species requires color film at a

photoscale of 1:1584 or larger. Even on color

film, the 1:3960 scale produced fairly low accuracies

of interpretation (63 percent).

A recent forestry graduate, who had one previous course in forest photogrammetry, did as

accurate a job of interpreting at these scales as

did men having 20 years^ experience. This man

was given 3 days of intensive training on sample

trees and sample photography before taking the

test. Thus, the interpreter's experience can be

disregarded as a variable in interpreting largescale color transparencies if proper training and

training aids are used.

The cost of using color film at large scales should

be little more than that required for panchromatic

film. While color film costs five times as much as

panchromatic film, the important point is that

film cost is only a small part of the total cost of

14
aerial photography. When the equal aircraft

costs, the same standby time for the flight crew,

elimination of the need for prints, and reduction of

photo handling by interpreting color film in rolls

are considered, the extra cost of the color film is

minor. Increased interpretation accuracy on color

film would counterbalance the slight increase in

cost.

Tree species were identified accurately enough

on color film at large scales to suggest the possibility of using it on actual inventory problems.

Further study of hardwoods, especially to associate their crown and foliage characteristics with

age and physiographic features, should be helpful

in improving identification of these tree species.

Literature Cited

(1) Aldrich, R. C, Bailey, W. F., and Heller, R. C.

1959. Large-scale 70-mm. color photography

techniques and equipment and their

application to a forest sampling

problem. Photogrammetrie Engin.

25(5): 747-754.

(2) American Optical Company.

1940. Pseudo-isochromatic plates for testing

color perception. 11 pp., illus.

Southbridge, Mass.

(3) Dimmick, F. L.

1942. The International Society Color Council color aptitude test. Optical Soc.

Amer. Jour. 32: 745. (Abstract.)

(4) Evans, R.

1948. An introduction to color. New York:

John Wiley & Sons, Inc. 340 pp.

(5) Munsell Color Company.

Munsell book of color. Ed. 1920-60.

Baltimore: Munsell Color Co., Inc.

(6) Nickerson, D.

1940. History of the Munsell Color System

and its scientific application. Optical Soc. Amer. Jour. 30: 575-586.

(7)

1958. Color measurement and its application

to the grading of agricultural products. U.S. Dept. Agr. Misc. Pub.

580, 62 pp.

(8) Snedecor, G. W.

1956. Statistical methods. Ed. 5, 534 pp.

Ames: Iowa State College Press.

(9) U.S. Department of Agriculture, Forest Service.

1958. Timber resources for Americans future.

Forest Res. Rpt. 14, 713 pp., illus.

15
ON

Appendix

SPECIES ARRANGED ACCORDING TO MOST ]FREQUENTLY IDENTIFIED FEATURES ON COLOR PHOTOGRAPHS (1:1584 SCALE)—Con.

Conifers (0 weight) Hardwoods (100 weight)

Identifying features

Abies

balsamifera

Picea

glauca

Picea

mariana

Pinus

strobus

Thuja

occidentalis

Pinus

resinosa

Pinus

banksiana

Populus

balsamea

Populus

tremuloides

Betula

papyrifera

Acer

rubrum

Weight

Crown apexes:

Acuminate _ X 1 Acute _ X X ________ X 9

Obtuse _ 3

Narrowly rounded __ A

Broadly rounded __ _ X X X X X ________

X

5

6

7

Flat

Indefinite __ _ __ _

Crown margins:

Entire _ X I

Sinnuate __ __ X

X

X

X

X ________

X

X

X

X

X

X

X

X

X

X

X

2

3

A

Finely serrate __ _ ____ X

X

X

Coarsely serrate _

Lobed X X 5

Parted

Foliage arrangement:

Conifers:

Light tip to bole _ _ X 1

Layered branches _ _ X 2

X

X

X

Wheel spokes _ X

X

X

3

Columnar branches _ A

Large triangular branches 5

Small clumps __ _ X 6

Small light spots __ X 7

Starlike top X S

Dark spot in clump _ X 12

Fine texture and scraggly branches. _ X 16

Hardwoods:

Small light spots X 1

Small clumps X

X

X

2

Occasional long branches 3

Limbs show (old trees) _ X

X

X

"""x""

4

Large foliage masses Q

Fine texture _ 7

Columnar branches _ 9

Color attributes:

Hue:

5 green I

2.5 green _ _ X 2

10 green yellow _ _ _ X 3

7.5 green yellow X X 4

5 green yellow X 5

2.5 green yellow __ _ _ X X X 6

10 yellow __ X 7

7.5 yellow X X 8

9

5 yellow
SPECIES ARRANGED ACCORDING TO MOST FREQUENTLY IDENTIFIED FEATURES ON COLOR PHOTOGRAPHS (1:1584 SCALE)—Con.

Value :

5 _ _ _ 1

6___ _ __ _-_ X 2

7 X ________ X X X X 3

8 X X X X 4

Chroma :

2_ _ 2

4 X X X

_

4

6 _ _ ___ X X X X X X X ________ 6

8 8

Average sum of weights __ 14 19 21 25 30 35 42 123 125 128 139