The Accuracy of Selected Land U!re and 

Land Cover Maps at Scales of 1:2f'l,OOO 

and 1 :100,000 

By Katherine Fitzpatrick-Lins 

GEOLOGICAL SURv·ey c-IRCULAR 829 

1980 
United States Department of the Interior 

Cecil D. Andrus, Secretary 

Geological Survey 

H. William Menard, Director 

Library of Congress Cataloging in Publication Data 

Fitzpatrick-Lins, Katherine. 

The accuracy of selected land use and land cover maps at scales of 1:250,000 and 1:100,000. 

(U.S. Geological Survey circular; 829) 

Bibliography: p. 

1. Land use-United States-Maps. 

I. Title. II. Series: United States. Geological Survey. Circular; 829. 

QE75.C5 no. 829 [HD205 1980] 557.3s 

Free on application to Branch ot Distribution, Geological Survey, 

604 South Pickett Street, Alexandria, VA 22304 

[333.73'13) 80-607906 
Table of Contents 

Page 

Abstract ------------------------------------------------------------------- 1 

Introduction ---------------------------------------------------------------- 1 

Sample selection ------------------------------------------------------------ 2 

Accuracy determination for the map------------------------------------------ 4 

Accuracy determination for the categories ------------------------------------ 4 

Accuracy assessment -------------------- ------------------------------------ 5 

Tampa ------------------------------------------------------------------- 5 

Portland ----------------------------------------------------------------- 8 

Charleston --------------------------------------------------------------- 9 

Greeley ------------------------------------------------------------------ 13 

Atlanta ------------------------------------------------------------------ 14 

Seattle and Tacoma ------------------------------------------------------- 18 

Combined results ----------------------------------------------------------- 21 

Conclusions ---------------------------------------------------------------- 23 

References ----------------------------------------------------------------- 24 

Illustrations 

Page 

FIGURE 1. Classification error matrix of predictable errors ------------------------ 3 

2. Classification error matrix of the Tampa, Florida, land use and land cover 

map ----------------------------------------------------------- 7 

3. Classification error matrix of the Portland, Maine, land use and land cover 

map ----------------------------------------------------------- 10 

4. Classification error matrix of the Charleston, West Virginia, land use and 

land cover map -------------------------------------------------- 12 

5. Classification error matrix of the Greeley, Colorado, land use and land cover 

map ----------------------------------------------------------- 15 

6. Classification error matrix of the Atlanta, Georgia, land use and land cover 

map ----------------------------------------------------------- 17 

7. Classification error matrix of the Seattle, Washington, land use and land 

cover map ------------------------------------------------------ 19 

8. Classification error matrix of the Tacoma, Washington, land use and land 

cover map ------------------------------------------------------ 20 

9. Classification error matrix of the combined results --------------------- 22 

Table of Contents iii 
Tables 

Page 

TABLE 1. Land use and land cover classification system for use with remotely sensed 

data ----------------------------------------------------------- 2 

2. The number of polygons, the area, and the percentage of area in each 

category with the number of sample points selected and the percentage 

of points for the land use and land cover map, Tampa, Florida, 1972 _____ 6 

3. Major land use and land cover categories on the Tampa map analyzed for 

errors of commission -------------------------------------------- 8 

4. Major land use and land cover categories on the Tampa map analyzed for 

errors of omission ----------------------------------------------- 8 

5. Major land use and land cover categories on the Portland map analyzed for 

errors of commission ------------------------.-------------------- 9 

6. Major land use and land cover categories on the Portland map analyzed for 

errors of omission ----------------------------------------------- 9 

7. Major land use and land cover categories on the Charleston map analyzed 

for errors of commission ------------------------------------------ 11 

8. Major land use and land cover categories on the Charleston map analyzed 

for errors of omission -------------------------------------------- 11 

9. Major land use and land cover categories on the Greeley map analyzed for 

errors of commission -------------------------------------------- 14 

10. Major land use and land cover categories on the Greeley map analyzed for 

errors of omission ----------------------------------------------- 14 

11. Major land use and land cover categories on the Atlanta map analyzed for 

errors of commission -------------------------------------------- 16 

12. Major land use and land cover categories on the Atlanta map analyzed for 

errors of omission ----------------------------------------------- 16 

13. Major land use and land cover categories on the Seattle map analyzed for 

errors of commission -------------------------------------------- 18 

14. Major land use and land cover categories on the Tacoma map analyzed for 

errors of commission -------------------------------------------- 21 

15. Major land use and land cover categories of the Seattle map analyzed for 

errors of omission ----------------------------------------------- 21 

16. Major land use and land cover categories on the Tacoma map analyzed for 

errors of omission ----------------------------------------------- 21 

17. Accuracy of combined data: errors of commission-------------------- 21 

18. Accuracy of combined data: errors.of omission----------------------- 23 

19. Land use and land cover map accuracies for selected maps-------------- 23 

iv Accuracy of selected maps 
The Accuracy of Selected Land Use and Land Cover 

Maps at Scales of 1:250,000 and 1:100,000 

By Katherine Fitzpatrick-Lins 

Abstract 

Land use and land cover maps produced by the U.S. 

Geological Survey are found to meet or exceed the 

established standard of accuracy. When analyzed using a 

point sampling technique and binomial probability theory, 

several maps, illustrative of those produced for different 

parts of the country, were found to meet or exceed accuracies of 85 percent. Those maps tested were Tampa, 

Fla., Portland, Me., Charleston, W.Va., and Greeley, 

Colo., published at a scale of 1:250,000, and Atlanta, Ga., 

and Seattle and Tacoma, Wash., published at a scale of 

1:100,000. For each map, the values were determined by 

calculating the ratio of the total number of points correctly interpreted to the total number of points sampled. Six 

of the seven maps tested have accuracies of 85 percent 

or better at the 95-percent lower confidence limit. 

When the sample data for predominant categories 

(those sampled with a significant number of points) were 

grouped together for all maps, accuracies of those 

predominant categories met the 85-percent accuracy 

criterion, with one exception. One category, Residential, 

had less than 85-percent accuracy at the 95-percent lower 

confidence limit. Nearly all residential land sampled was 

mapped correctly, but some areas of other land uses 

were mapped incorrectly as Residential. 

Introduction 

A Level II land use and land cover 

classification system for use with remotely 

sensed data (Anderson and others, 1976) is 

being used for maps at scales of 1:250,000 

and 1:100,000. The maps were prepared with 

manual interpretation of high-altitude aerial 

photographs by the U.S. Geological Survey. 

Sca~e-stable copies of the topographic map 

base were used as a mapping base. The land 

use and land cover classification is shown in 

table 1. The minimum mapping area according to the specifications is 16 hectares for 

most categories and 4 ha for Urban or BuiltUp Land and such selected categories as 

Confined Feeding Operations (23), Other 

Agricultural Land (24), Water (53-54), Strip 

Mines, Quarries, and Gravel Pits (75), and 

Transitional Land, if urban (76) (Loelkes, 1977). 

Certain of the mapping criteria adhered to, 

specified by Anderson and others (1976), 

stated that (1) the land use and land cover 

maps must be at least 85-percent accurate, (2) 

the accuracy of the interpretation will be 

about equal for the several categories, and (3) 

the results must be repeatable from interpreter to interpreter and from one time to 

another. Once the maps were compiled, field 

verification was conducted to assure correct 

interpretation, and the maps were made 

available to local users for review. Additional 

corrections were then incorporated. 

Ideally, any land use and land cover 

classification system designed should have 

categories that are mutually exclusive. l''one 

the less, there are some categories in ary 

system whose identifying signatures can be 

confused with others or whose function~ so 

closely resemble others that confusion occurs. For this reason, a classification er·or 

matrix is useful in recognizing where and why 

errors occur. For the system employed t ., the 

Geological Survey, experienced interpreters 

can often predict which categories will t1~ in 

error. Usually these errors are expected within 

a Level I category or between two or mo"e 

Level II categories that have similar visual 

signatures or characteristics. 

Certain of these predictable errors mE" not 

affect the useability of the land use and land 

cover map for some purposes. For exam pie, 

an agency estimating the forest area on a 

map might not be concerned with the separation of deciduous and evergreen tree types. 

When the two categories of industrial and 

commercial land are intermixed in an in· 

dustrial park, a planner might not be concerned as to whether the area is classiF~d as 

Commercial (12) or Industrial (13). Some categories such as Cropland and Pasture (21) and 

Other Urban or Built-Up Land (17) often differ 

only in where they are located. The lane cover 

may be the same. It is helpful, therefore, for 

the user to know, not only how accurate the 

map is but what kinds of errors occurre~. 

Introduction 1 
TABLE 1.-U.S. Geological Survey land use and land cover 

classification system for use with remotely sensed data 

[From Anderson and others, 1976] 

Levell Level II 

1 Urban or Built-Up Land _ 11 Residential 

12 Commercial and Services 

13 Industrial 

14 Transportation, Communications, and Utilities 

15 Industrial and Commercial 

Complexes 

16 Mixed Urban or Built-Up 

Land 

17 Other Urban or Built-Up 

Land 

2 Agricultural Land ----- 21 Cropland and Pasture 

22 Orchards, Groves, Vineyards, Nurseries, and 

Ornamental Horticultural 

Areas 

23 Confined Feeding Operations 

24 Other Agricultural Land 

3 Rangeland ----------- 31 Herbaceous Rangeland 

32 Shrub and Brush Rangeland 

33 Mixed Rangeland 

4 Forest Land ---------- 41 Decidous Forest Land 

42 Evergreen Forest Land 

43 Mixed Forest Land 

5 Water --------------- 51 Streams and Canals 

52 Lakes 

53 Reservoirs 

54 Bays and Estuaries 

6 Wetland ------------- 61 Forested Wetland 

62 Nonforested Wetland 

7 Barren Land ---------- 71 Dry Salt Flats 

72 Beaches 

73 Sandy Areas Other Than 

Beaches 

7 4 Bare Exposed Rock 

75 Strip Mines, Quarries, and 

Gravel Pits 

76 Transitional Areas 

77 Mixed Barren Land 

8 Tundra -------------- 81 Shrub and Brush Tundra 

82 Herbaceous Tundra 

83 Bare-Ground Tundra 

84 Wet Tundra 

85 Mixed Tundra 

9 Perennial Snow or Ice __ 91 Perennial Snowfields 

92 Glaciers 

2 Accuracy of selected maps 

Figure 1 is a classification error matrix highlighting those categories that are most in error because of the definition of the categories. The degree of difficulty of differentiating among these categories differs from one 

area of the country to another depe'1ding on 

the intermixture of land use patterrs and 

vegetation types. 

This research project was undertaken to 

study quantitatively and objectively the accuracy of the Level II land use and land cover 

maps and to see if the mapping criteria were 

being met. From maps of different geographic 

regions and from maps believed to be characteristic of the map products as a whole, it 

was possible to determine the map accuracy 

and to conclude whether or not the mapping 

accuracy criteria were being met. It was also 

possible to show through classification error 

matrices the types of errors that had 

occurred. 

Sample Selection 

For this research project to assess accuracy for selected land use and land cover 

maps across the country, the Tampa, Fla., 

Portland, Me., Charleston, W. Va., and 

Greeley, Colo., maps were selected as examples of the 1:250,000 scale. Atlanta, Ga., 

and Seattle and Tacoma, Wash., maps were_ 

selected as examples of these maps at 

1:100,000 scale. Specifications for compilation 

were the same for the 1:1 00,000-scc: 'e and the 

1 :250,000-scale maps, and, so, the only compilation difference was format. Seattle and 

Tacoma are formatted as 0.5 o (latitude) x 1 o 

(longitude) maps. The standard 1:250,000 

quadrangles are 1 o x 2° maps, whereas the 

Atlanta map is in a special format '''hich is 

centered on the city of Atlanta. 

Previous analyses demonstrated that the 

best method for determining accurc~Y was by 

sample points selected according to a stratified systematic unalined sampling design 

(Fitzpatrick-Lins, 1978). The land use and land 

cover map was first stratified into 10- x 

10-kilometer blocks coinciding with the Universal Transverse Mercator grid system. 

Within the 10-km blocks, points at t"le intersection of a 1-km grid cell were S'~lected 
ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

z 

0 

j::: 

<( 

1-

w 

a: 

a. 

a: 

w 

1-

z 

0 

w 

u:: 

~ w 

> 

11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

33 

41 

42 

43 

51 

52 

53 

54 

61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

-

IS 

-

I I 

FiGURE 1.-Ciassificatlon error matrix of predictable errors. The shaded areas indicate the most likely error types. The 

diagonal Is the line of concurrence between the original interpretation and the verified interpretation. For the definition 

of the numerical categories, see table 1. 

for each block by a systematic unalined sample. If a point fell on a boundary between two 

categories, it was considered as two points 

so both interpretations could be checked. 

Each point was examined independently and 

cross~checked against the original photographs. Any point not easily interpreted would 

be field-verified when necessary. The points 

were considered accurate when the original 

mapped interpretation agreed with that of the 

accuracy interpreter. If the land use and land 

cover codes differed, then the original interpretation was considered in error; if they 

agreed, then the point was considered to be 

correct. In this way, only two possibilities existed, either the points examined were correct 

Sample selection 3 
(1) or they were incorrect (0). For this reason, 

the binomial probability theory was applicable 

for determining the number of points to be 

tested and for determining accuracy. Accuracies were calculated as r/n, the total 

number of points correct (r}, divided by the 

total number of points (n), and expressed as a 

percentage. 

The ideal number of points to be tested per 

map was determined from the formulas for 

the binomial probability theory. The formula 

for the number of points selected was 

N=~' E2 

''ihere p is the expected percent accuracy, q 

Is the difference between 100 and p,· E is the 

allowable error, and N is the number of points 

to be sampled (Snedecor and Cochran, 1967, 

p. 517). 

For a sample where we expected accuracies of 85 percent and an allowable error of 

4 percent (2 standard deviations of 2 percent), 

the number of points necessary for reliable 

results would be 

N 4(85 X 15) 

42 

or 319 points. Fewer points could be sampled 

if the accuracy was assumed to be greater 

than 85 percent or the standard deviation acceptable was larger. We selected the 

85-percent expected accuracy because the 

land use classification system specifies that 

each category should be mapped to at least 

an 85-percent accuracy. The narrow limits of a 

2-percent standard deviation were selected 

because the methods of sampling involved 

very little field work and, therefore, should be 

a precise as possible to offset any procedural 

errors. As there was very little field work, 

costs were mini·mal, and a large sample increased the possibility of sampling an adequate number to test the major categories on 

the map. The standard error acceptable for 

each category was set at 10 percent. 

With expected map accuracies of 85 percent and an acceptable error of 10 percent, 

the sample size for each map should be at 

least 50. As the expected accuracies increase, the sample size required decreases. 

According to Van Genderen and Lock (1977), 

the smallest sample size for meaningful 

4 Accuracy of selected maps 

results is 20 points, even if the sample is 

error free. 

Accuracy determination for the map 

Once the sample was selected, the points 

were examined for correctness of interpretation. The ratio, p (expressed as a percent), of 

the number of points correct, r, to the total 

number of points, n, was the accuracy value 

for the map. As this value is the test value for 

comparison to the minimum standard of 

85-percent accuracy, a one-tailed test is appropriate. The 95-percent one-tailed lower confidence limit -for a binomial distributions is 

obtained from the equation (derived from 

Snedecor and Cochran, 1967, p. 211): 

p = p - { 1.645 ""pq/n + 50/n }, 

where p = the accuracy of the map expressed 

as a percent; p = the sample value of p or r/n expressed as a percent; 

q = 100-p; and 

n = the sample size. 

If the p value exceeds the 85-percent criterion 

at the lower confidence limit, we may accept 

with 95-percent confidence that the maps 

meet or exceed the accuracy standards. This 

is not to say that those maps that fall short of 

85-percent accuracy at the lower confidence 

limit do not meet the accuracy standards, but 

that we have less confidence that they do. In 

fact, there is still a possibility that they exceed it. 

Accuracy determination for the categories 

For the set of sample points for each map 

sheet, a classification error matrix was constructed showing how reliably each category 

was interpreted and where the misinterpretations occurred. Although there was a simple 

accuracy statement with a given lower confidence limit for each map, there were two 

ways of expressing the percent accuracy of 

each category-as analyzed for errors of commission and as anlayzed for errors of omission. For many users of land use and land 

cover data, the question is how well did the 

categories as mapped depict the real world, 

or what was the probability of an error of 

commission? This value can be obtained from 

the ratio of the number of points correct for 
each category to the total number of points 

for each category sampled from the map. 

Another pertinent question less often addressed is how well was the real world 

depicted by the map, or what were the probabilities of an error of omission? This value 

can be obtained from the ratio of the number 

of points correct for each category to the 

total number of points for each category 

found in the verification process. 

By definition, the sample was designed to 

select from map data, and, so, we chose to 

consider primarily the errors of commission. 

Once these data were analyzed and compared 

to the verified interpretation, an estimate of 

the errors of omission was obtained. For each 

analysis, a two-tailed test was used to find 

the true range of value for errors of commission and errors of omission. Neither of these 

estimates can stand alone as the accuracy of 

the category. It was also possible to compare 

the c~assification error matrix for each map 

sheet ·with the error matrix of most likely 

misinterpretations to see if the interpretation 

difficulties were predictable. 

The maps produced at 1:100,000 scale are 

easier for the user to read, but the information content is the same as the maps at 

1 :250,000 scale. For the purposes of the accuracy study, the scale consideration was 

negligible, as all verification was done at the 

compilation scale. For the maps discussed, 

the compilation scale was about 1:125,000. 

For this reason, no comparison of the results 

for different scales was performed. 

Accuracy Assessment 

Tampa 

The Tampa, Fla., land use and land cover 

map was produced at the same scale and format as the 1 :250,000-scale topographic map 

base. The nonocean part of the Tampa land 

use and land cover map portrays about 8,981 

square kilometers (7,209 km 2 of land categories), extending from the city of Tampa to 

south of Sanibel Island and including the 

metropolitan areas of Tampa, Sarasota, and 

Bradenton. The source material for the compilation was a set of 1 :80,000-scale black-andwhite transparencies copied from quadcentered color-infrared high-altitude ph,.,tographs. Compilers mapped the land use and 

land cover at 1:125,000 scale using an anlarged copy of the topographic map as a base 

with copies of the black-and-white transparencies at 1:125,000 scale. The minimum mapping unit was 16 ha for most categorier and 4 

ha for Urban or Built-Up Land (11-17) and 

such selected categories as Confined Feeding Operations (23), Other Agricultural Land 

(24), Water (52-54); Strip Mines, Quarries .. and 

Gravel Pits (75), and Transitional Areas (if urban) '76) (Loelkes, 1977). 

In the Tampa area, there was a difficulty in 

distinguishing Herbaceous Rangeland (31) 

from Nonforested Wetland (62) using tl1e 

photographs. Often the only way to distinguish between the two was to determire 

whether there was standing water by detecting sun glint. Transition areas were also 

causes of difficulty. Forested Wetland (61) 

often bordered Nonforested Wetland (62). Tall 

wetland grasses were mixed with brust'y mangrove areas. The signature of the forested 

category usually predominated even in areas 

where the mangrove had died leaving only 

bare bushes mixed with tall grasses. Another 

transition area was from Herbaceous Rangeland (31) to Evergreen Forest Land (42). The 

categories are not always mutually exc•usive, 

so that a particular interpreter's favoring of 

one category when drawing a boundary in a 

transition area was no more correct or incorrect than favoring another category. 

As mentioned earlier, points were se•~cted 

using a stratified systematic unalined rample. 

A total of 311 points were selected. Wl1en a 

point fell on a boundary, it was considered as 

two points. There were 43 boundary points on 

the Tampa map, making a total of 354 points. 

For the Tampa land use and land cov~r 

map, a computer printout of data from the 

digitized land use and land cover map was 

available. It was possible, therefore, to compare the number of points selected with the 

actual number of hectares in each category. 

The point sample shown in table 2 prov~d to 

be representative of the major categories on 

the map. The percentage of area and of 

points for each category compare favorably. 

By applying a Spearman Rank Correlation Test 

to compare the number of points samp'o.d 

Accuracy assessment 5 
TABLE 2.-The number of polygons, the area, and the percentage of area in each category with the number of sample 

points selected and the percentage of points for the land use and land cover map, Tampa, Fla., 1972 

Category Polygon Area 

(No.) (ha) 

11 411 82,092 

12 295 12,519 

13 43 3,854 

14 74 6,510 

15 4 893 

16 11 596 

17 207 7,378 

21 457 177,392 

22 424 31,189 

23 6 177 

24 108 1,397 

31 224 208,255 

32 12 1,072 

33 6 304 

42 534 55,825 

43 4 148 

51 33 5,589 

52 201 3,903 

53 82 2,053 

54 19 177,077 

61 585 67,219 

62 262 12,574 

72 46 2,870 

73 16 981 

75 30 5,866 

76 166 30,322 

Total 4,260 898,055 

with the area of each category, we were able 

to assume an association between the number of points and the area of each category. 

The null hypothesis of no association was re· 

jected with less than 0.001-percent probability 

of error, indicating that this method of selecting a sample is area weighted, which is not 

at all surprising. 

The table shows that only the predominant 

categories are sampled with sufficient points 

for adequate analysis. Many of the categories 

that occur occupy only a small percentage of 

the map area and that infrequently are not 

sampled or are sampled with too few points 

to determine their accuracy. Methods are currently being developed to utilize a computer 

program to sample all categories adequately 

for each map. This system will be applicable 

to any map that has been digitized and the 

data stored on a computer tape. 

Of the 354 points sampled on the Tampa 

land use and land cover map, 329 (93 percent) 

were found to be correct. The 95-percent one• 

tailed lower confidence limit for these data 

would be 91 percent, and, so, the accuracy of 

the overall land use and land cover map is 

6 Accuracy of selected maps 

Area Points Points 

(percentage) (No.) (p~rcentage) 

9.14 29 9.3 

1.39 4 1.3 

.42 2 .6 

.72 2 .6 

.10 

.07 

.82 3 1.0 

19.75 42 13.5 

3.47 13 4.2 

.02 1 .3 

.16 

23.19 90 28.9 

.12 

.03 

6.21 16 5.1 

.02 

.62 

.43 

.23 

19.72 60 19.3 

7.49 27 8.7 

1.40 2 .6 

.32 1 .3 

.11 1 .3 

.65 2 .6 

3.38 16 5.1 

99.98 311 99.7 

well above the acceptable accuracr of 85 percent. 

It is understandable that water categories, 

particularly category 54, were almo~t always 

mapped correctly. Considering that errors 

were practically limited to the land~based 

categories, it was interesting to consider only 

the land area categories. Of the 35.tt points, 65 

points were classified as category 54. (This 

doe not include any large bodies of other than 

inland water such as the Gulf of Mnxico.) Of 

the remaining 289 points from the land surface, 25 were in error and 264 were correct. 

For this land area, the accuracy percentage is 

91 percent with a 95-percent one-tailed lower 

confidence limit of 87 percent, still in excess 

of the required value of 85 percent. This particular analysis of only land area was necessary to determine if the large portion of the 

map showing water might have led to an inflated value of accuracy when considering the 

accuracy of the overall map. Although the 

map appeared more accurate when the water 

category was included, the map wa~ still 

above the specified accuracy of 85 percent in 

the land area only. 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 1-

~ 42 w 

b: 43 a: 

~51 

~ 52 0 

~53 lL 

0: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

28 

5 1 

2 

2 

3 1 

47 2 3 

2 1 16 1 

1 1 96 

1 20 

1 

65 1 

1 27 1 

1 1 

2 

33 5 2 2 0 0 3 49 16 1 0 101 0 0 0 21 0 0 1 0 65 31 3 0 

1 

1 

1 

--~ 

--- --r--

--r--

--~ 

--r---

--f--

--r--

--f--

1 --r--

--f--

--r--

--r--

--r--

--r--

- -

- -

- ~ 

- r---

- ~ 

---

----

----

---- 1 ---- 1 15 ---- : __ -

---

---

---

---

~--

0 2 17 0 0 0 0 0 0 

29 

6 

2 

0 

0 

4 

52 

20 

0 

0 

99 

0 

0 

0 

21 

0 

0 

0 

66 

30 

0 

0 

0 

18 

0 

0 

0 

0 

0 

0 

329 Correct 

354 Total 

FIGURE 2.-Ciassification error matrix of the Tampa, Fla., 1:250,000-scale land use and land cover map. For the definition of the numerical categories, see table 1. 

Accuracy assessme.,t 7 
A classification error matrix of the results 

for the Tampa land use and land cover map is 

shown in figure 2. 

The major land use and land cover categories on the Tampa map were analyzed for 

errors of commission (table 3). 

TABLE 3.-Major land use and land cover categories on the 

Tampa map analyzed for errors of commission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits1 

(percentage) 

11 Residential _____ 28 33 85 73- 99 

21 Cropland and 47 49 96 89-100 

Pasture. 

31 Herbaceous 96 101 95 90-100 

Rangeland. 

42 Evergreen Forest 20 21 95 88-100 

Land. 

54 Bays and 65 65 100 98-100 

Estuaries. 

61 Forested Wetland 27 31 87 75- 99 

1 The formula for the 95-percent confidence limits using a twotailed test is 

p = p±{1.96 ~+50/n}. 

The categories providing a reliable estimate 

of the true percentage correct with a 95-percent lower confidence limit within ± 10 percent are Cropland and Pasture (21), Herbaceous Rangeland (31), and Bays and Estuaries (54). Of these categories, all met the 

criterion of at least 85-percent accurate. 

When the data were examined for errors of 

omission from the point of view of the number of ground truth points for each category 

correctly identified on the map, the results 

differ somewhat (table 4). For instance, the 

number of points of Residential found during 

field work were sufficient to provide an 

estimate of the accuracy with ± 10 percent, 

TABLE 4.-Major land use and land cover categories on the 

Tampa map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 28 29 97 89-100 

, 21 Cropland and 47 52 87 77- 97 

Pasture. 

31 Herbaceous 96 101 95 90-100 

Rangeland. 

42 Evergreen Forest 20 21 95 88-100 

Land. 

54 Bays and 65 66 98 94-100 

Estuaries. 

61 Forested Wetland 27 30 90 78-100 

I 

8 Accuracy of selected maps 

whereas the ratio of correct points to the map 

sample points of Residential was too low to 

provide reliable results. In contrast, Cropland 

and Pasture appeared to be mapped with less 

accuracy when the actual occurren~e of this 

category in the field was compared to the 

number of occurrences mapped. Whereas 52 

of the field-checked points were in Cropland 

or Pasture, only 47 points were identified as 

such. From this viewpoint, it is app~rent that 

some cropland and pasture was ovarlooked. 

Portland 

The Portland, Me., land use and land cover 

map was produced at the same scale and format as the 1 :250,000-scale topogra~~ic map 

of Portland, Me. The land area is 15,038 km 2 

and includes the area from coastal New 

Hampshire at Portsmouth to north of 

Portland, Me. At the interior of the map sheet 

are Sebago Lake, Me., and Lake Winnipesaukee, N.H. The towns of Laconia and Franklin, the city of Concord, and the northern portion of Manchester, N.H., are also included. 

The terrain is hilly to mountainou~ with 

many small lakes. The urban areas are not 

large, there is relatively little cropland, and 

most of the area is forested. The most serious 

interpretation problem encountered by the 

compilers was one of separating the forest 

types. 

The Portland land use and land cover map 

was compiled using the 1:250,000-sc-:ale topographic map base enlarged to a scale of 

1:128,000. The land use and land cover source 

materials were black-and-white quad-centered 

photographs at a scale of 1:80,000 c':ltained in 

1973,. 1974, and 1975 along with copies of the 

same prints reduced to a scale of 1:128,000. 

Where this coverage was limited, 1~73 colorinfrared photographs at an approximate scale 

of 1:128,000 served as the source material. 

Two small areas of the map for which conventional source material was not available were 

compiled at the Survey's Special Mapping 

Center in Reston, Va. Once the land use and 

land cover data were compiled, the finished 

maps were reduced to a scale of 1:~~1),000. 

The land use and land cover map was 

evaluated for accuracy at the scale of compilation using the same photographs used for 
the original interpretation. The source material for that portion of the map compiled at the 

Special Mapping Center was not available 

and so that portion was not evaluated for accuracy. 

A total of 456 points were selected according to a stratified systematic unalined sample. Each point was reexamined on the photographs and compared to the original interpretation. Where any interpretation difficulties 

remained, the actual land use or land cover 

was verified in the fields. 

Of the total 456 points verified in the 

Portland land use and land cover map, 410 (90 

percent) were found to be correct. At the 

95-percent one-tailed lower confidence level, 

the lower limit of true accuracy was 87 percent. This value was well above the acceptable accuracy of 85 percent. When the land 

use and land cover categories were considered (excluding category 54, which is not 

part of the land area of the sheet and not 

usually subject to interpretation errors), the 

accuracy of the map remained at 90 percent 

(402 correct of 448 total points) with a 

95-percent one-tailed lower confidence limit of 

87 percent. From this, it was apparent that 

the number of sample points in the water 

category 54 did not bias the results on this 

map sheet. The classification error matrix for 

Portland, Me., is shown in figure 3. 

The major land use and land cover categories examined for errors of commission for 

the Portland, Me., sheet are shown in table 5. 

TABLE 5.-Major land use and land cover categories on the 

Portland map analyzed for errors of commission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 29 36 81 66- 95 

21 Cropland and 25 26 95 86-100 

Pasture. 

41 Deciduous Forest 28 32 88 74-100 

Land. 

42 Evergreen Forest 75 88 85 77- 93 

Land. 

43 Mixed Forest 204 213 95 92- 98 

Land. 

Only Cropland and Pasture (21), Evergreen 

Forest Land (42), and Mixed Forest Land (43) 

were reliable with ± 10 percent of the sample 

results. Of these, Evergreen Forest Land (42) 

fell short of the acceptable accuracy of 85 

percent at the lower confidence limit. The 

most frequent misclassification of thif 

category was that is was mapped as Mixed 

Forest Land (43). 

When the data were examined for errors of 

omission rather than errors of commis~ion, 

the results for these same categories were as 

shown in table 6. 

TABLE 6.-Major land use and land cover categories on the 

Portland map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(pNcentage) 

11 Residential _____ 29 31 94 82-100 

21 Cropland and 25 27 93 81-100 

Pasture. 

41 Deciduous Forest 28 34 82 68- 97 

Land. 

42 Evergreen Forest 75 81 93 87- 99 

Land. 

43 Mixed Forest 204 223 91 88- 95 

Land. 

Those categories having accuracy pP.rcentage with ± 10 percent were Evergreen Forest 

Land (42) and Mixed Forest Land (43). 

Residential (11), Cropland and Pasture (21), 

and Deciduous Forest Land (41) have too wide 

a confidence interval for reliable result~, 

Residential appeared to be interpretod more 

correctly when compared to the actual 31 

points of Residential found in the field than 

when compared to the 36 points of ma"lped 

Residential. In all probability, Resident 1

al is 

overestimated on the map. The interprfltation 

of Evergreen Forest Land also appeare1 to be 

more precise when compared to the fie1d data 

than when compared to the map data. Much 

of the land interpreted as Evergreen Fc"est 

Land was actually Mixed Forest Land. 

Charleston 

The Charleston, W.Va., land use and land 

cover map, at the same scale and formqt as 

the Charleston, W.Va., 1:250,000-scale topographic map, encompasses 19,352 km2 in the 

heart of West Virginia. The land is mostly 

forested mountainous terrain transecte1 by 

the Kanawha River, which is visible in the 

lower left corner of the map. Charleston, the 

capital of West Virginia and the only major 

city on the map, is at the intersection of the 

Kanawha and Elk Rivers. The area of tr~ map 

Accuracy assessment 9 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 1-

~ 42 w 

g: 43 

a: 

~51 

~ 52 0 

~ 53 u. 

~ 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

29 1 1 0 

1 3 1 0 1 

1 0 I 

6 

3 

2 25 

1 

0 

0 0 

1 0 

0 0 0 

1 28 1 4 

2 75 4 

4 3 12 204 

2 

17 2 

8 

1 1 5 

2 3 

0 

1 

38 4 6 0 1 4 26 1 0 1 0 0 0 32 88 213 2 17 2 8 7 3 0 0 0 0 1 0 0 0 0 0 0 

31 

6 

6 

0 

0 

3 

27 

0 

0 

0 

1 

0 

34 

81 

22 

1 9 

0 

8 

5 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

~Correct 

456 Total 

FIGURE 3.-Ciassification error matrix of the Portland, Me., 1 :250,000-scale land use and land cover map. For the definition of the numerical categories, see table 1. 

10 Accuracy of selected maps 
is predominantly forested with small rural 

settlements. 

The major categories on the land use and 

land cover map are Deciduous Forest and 

Mixed Forest Lands. Very little Cropland and 

Pasture is present; special specifications 

were created to map these areas to a mini-

. mum width of 200 meters instead of the usual 

400 m, so that the few existing agricultural 

areas would be mapped. 

Another land use type in this region given 

special consideration is the surface strip 

mine. Where the surface strip mined area was 

larger than 4 ha and a minimum of 90 m wide, 

it was mapped as category 75. Ordinarily, this 

category is mapped for a minimum of 4 ha 

but must be at least 200m wide. In evaluating 

the map for accuracy, these unique situations 

were taken into account, and care was taken 

to meet the same specifications. 

The land use and land cover map was compiled using 1:125,000-scale high-altitude colorinfrared photographs of September 1972 and 

December 1973. The Kern P.G. 2 stereoplotter1 

was used with the high-altitude photographs 

and the 1 :250,000-scale topographic map 

base, each at original scale. The stereoplotter 

allowed for stereoscopic viewing of the photographs and for adjusting this image to the 

scale of the map base for compilation. The 

photographs could also be enlarged to two, 

four, or eight times the original. 

After the original land use and land cover 

mapping was completed, a copy of the map 

was enlarged to a scale of 1:125,000, the 

same scale as the original photographs. For 

quality control, the photographs were registered to the enlarged map for direct comparison without the use of the P.G. 2 stereoplotter. The accuracy check involved this 

same technique, overlaying the photographs 

with the map, to verify the interpretation at 

selected sample points. 

The 424 sample points were selected using 

a stratified systematic unalined sample. The 

same specifications and special considerations approved for compilation were followed 

for the accuracy check. 

1 The use of brand names in this report is for identification purposes only and does not constitute endorsement by the U.S. 

Geological Survey. 

Of the 424 points checked for accuracy on 

the Charleston land use and land cover map, 

393 (93 percent) were found to be corre':t. The 

95-percent one-tailed lower confidence limit 

was 90 percent. The classification error matrix 

for Charleston is shown in figure 4. 

Of the 424 points checked, 353 were in two 

forest categories, Deciduous Forest (41) and 

Mixed Forest (43) Lands. The next significant 

category in the sample was Cropland and 

Pasture (21) with 53 points. Thus, 406 P">ints 

(96 percent) represent these three major land 

use categories. The results for each of these 

three categories analyzed for errors of commission are shown in table 7. Neither 

category 21 or category 43 is mapped '"ith the 

necessary accuracy of 85 percent at th~ lower 

confidence level. 

TABLE 7.-Major land use and land cover categor/es on the 

Charleston map analyzed for errors of commission 

95-percent 

Category Points Points Percent co.,fidence 

correct total correct limits 

(pe·centage) 

21 Cropland and 46 53 87 17- 97 

Pasture. 

41 Deciduous Forest 207 214 97 r·i-100 

Land. 

43 Mixed Forest 123 139 88 r.1- 94 

Land. 

When the sample was considered for errors 

of omission, these three categories we .. e 

found to have the accuracies shown in table 

8. 

TABLE B.-Major land use and land cover categories on the 

Charleston map analyzed for errors of omission 

91:--percent 

Category Points Points Percent c<lnfidence 

correct total correct limits 

(prrcentage) 

21 Cropland and 46 49 94 86-100 

Pasture. 

41 Deciduous Forest 207 229 90 86- 94 

43 Mixed Forest 123 127 97 93-100 

Land. 

All three categories above exceed th~ required accuracy of 85 percent at the lower 

confidence limit when examined for errors of 

omission. 

After comparing the tables of errors of 

omission and of commission, we reexamined 

the map data to analyze the difference and 

concluded that the size of smaller polygons 

Accuracy assessmert 11 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 I-

~ 42 w 

g: 43 

a: 

~51 

~ 52 0 

!:!::! 53 lL 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 8? 83 84 85 

4 2 

1 

2 

1 

46 3 

5 207 16 1 

2 

4 123 

3 

1 

3 

4 0 1 2 0 0 1 53 0 0 0 0 0 0 214 2 139 3 0 000000004 0 0 (l 0 0 0 

6 

0 

0 

0 

49 

0 

0 

0 

0 

0 

0 

229 

127 

3 

0 

0 

0 

0 

0 

0 

0 

0 

0 

3 

0 

0 

0 

0 

0 

0 

393 Correct 

424 Total 

FIGURE 4.-Ciassification error matrix of the Charleston, W.Va., 1:250,000-scale land use and land cover mRo. For the 

definition of the numerical categories, see table 1. 

12 Accuracy of selected maps 
of land use were increased even larger than 

the unique specifications would allow to insure their inclusion on the map, thereby decreasing the errors of omission for these categories but increasing the errors of commission. This practice appeared to be the primary 

cause of error for Cropland and Pasture (21); 

frequently, the surrounding Forest Land was 

included in the polygon mapped as Cropland 

so that the polygon would meet the minimum 

mapping size. 

Mixed Forest Land (43) was also less than 

85 percent accurate at the lower confidence 

limit. The primary cause of error in category 

43 appeared to be that it was often used for 

convenience even when the predominant 

forest type was Deciduous Forest Land (41). 

There were 16 sample sites where category 41 

was mapped as category 43. This error, one of 

misclassifying one forest type for another, 

might not be as serious from a users point of 

view as mistaking Forested Land for Cropland 

and Pasture. 

In spite of these specific error types, the 

overall accuracy of the Charleston land use 

and land cover map exceeded the required accuracy of 85 percent at the lower confidence 

level. 

Greeley 

The Greeley, Colo., land use and land cover 

map, 1979, at a scale of 1:250,000 is representative of the land use and land cover types of 

Colorado's eastern plains and mountain 

slopes. The land area of the map is 18,855 

km2

• The western portion of the map includes 

parts of the southern Rocky Mountains with 

their forest and alpine vegetation, and the 

eastern portion of the map is in the eastern 

plains of Colorado with its cropland, pasture, 

and rangeland vegetation. In the central portion of the map are the cities of Boulder, 

Longmont, Loveland, and Greeley, Colo. 

The compilers mapped the land use and 

land cover categories using high-altitude 

black-and-white photographic transparencies 

acquired in 1975 and 1976 as the primary 

source material. Reductions of these transparencies were overlaid with a copy of the 

topographic map base at a common scale of 

1:128,000. The land use and land cover compilation was made directly on the 1:128,001-

scale copy of the topographic base map. To 

assist in the interpretation, the compilers also 

employed high-altitude color or color-inf~ared 

transparencies. These photographs wer€ from 

1972 and were used only as auxiliary source 

materials to the more current black-and-white 

photographs. No stereo processes were employed during compilation, so registration 

was a problem in the mountainous regic'ls. 

Valley bottoms were often correctly registered, whereas the ridgelines were often misregistered. No measure of the resulting misregistration was made during the accuracy 

check. 

Specific problem categories for the interpreters using the black-and-white photo, 

graphs were in separating Cropland and 

Pasture (21) from Herbaceous Rangelan1 (31), 

separating Deciduous Forest Land (41) from 

Evergreen Forest Land (42), separating t"erbaceous Tundra (82) from Bare-Ground Tundra 

(83), and separating Herbaceous Rangeland 

(31) from Mixed Rangeland (33). 

In the eastern portion of the map, the 

rangeland may be either a shrub and br 1

·.•sh 

rangeland with much sagebrush and sand 

sages, rangeland of grasses and forbs, or a 

mixed rangeland. It was often not possible to 

recognize these vegetation types on the: 

photographs alone. The graininess of tt'~ film 

produced more texture than the pattern of 

vegetation types (Eldon Jessen, personal 

commun., 1978). 

Where range management was practiced, 

the signature of Herbaceous Range (31) was 

almost identical to that of Cropland and 

Pasture (21). For pasture to be classifie1 as 

category 21, it is required that it be in r~rmanent use and maintenance as pasture. Often, 

brush control was the only modification, and, 

therefore, the grazing land would be classified 

as Herbaceous Rangeland (31). In these areas, 

once the shrub brush had regrown, the proper 

category was Mixed Rangeland (33). 

Even cropland in the wheat areas is not permanent. Much former cropland has bee-'1 

abandoned and reverted to rangeland, and 

new areas of rangeland have been cultivated 

in wheat. Often cropland scars are app~rent 

long after the land has been allowed tc revert 

to rangeland. Abandoned cropland would be 

Accuracy assessment 13 
classified as Rangeland; however, fallow 

cropland would still be in the Cropland and 

Pasture category. 

Because of these difficulties in interpreting 

the land use and land cover categories in the 

eastern portion of the map, this area was extensively field checked at the time of compilation. The original field-check photographs 

were actually more beneficial to an accuracy 

check than current field work would have 

been, considering how transitional the land 

cover is. 

In the wes"'"fern portion of the map, the land 

cover is more static. Aspen was difficult to 

distinguish from the coniferous trees on the 

summer black-and-white photographs. The 

color-infrared photographs were the most useful for separating the Deciduous Forest (41) 

and Evergreen Forest (42) Lands. Herbaceous 

Tundra (82) and Bare-Ground Tundra (83) were 

difficult to separate on the black-and-white 

photographs. For these areas, the colorinfrared photographs were helpful. During the 

accuracy check, stereo viewing was also 

beneficial. 

According to a stratified systematic unalined sampling design, a sample of 375 

points was initially chosen. Of these, 38 fell 

on a boundary and were considered to be 

double points, giving a total of 413 points. 

Each point on the map was checked against 

the original compilation materials. Where 

questions occurred, the points were located 

on the 7.5-minute topographic map and 

checked against the original precompilation 

data by those who had spent time in the field. 

The result of the accuracy check of the 

Greeley, Colo., land use and land cover map 

is that the overall accuracy was 399 points of 

413 points total, or 97-percent correct with a 

95-percent one-tailed lower confidence limit of 

95 percent. This result far exceeds the expected accuracy of 85 percent. 

Of those categories with more than the required number of points to provide reliable accuracy data, the results for errors of commis .. 

sion are as shown in table 9. All these 

categories exceed the expected accuracy of 

85 percent at the lower confidence limit. 

When these same categories are considered from the point of view of errors of omission, or the field-identified points that were 

14 Accuracy of selected maps 

TABLE 9.-Major land use and land cover cat~gories on the 

Greeley map analyzed for errors of commission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

21 Cropland and 124 126 98 96-100 

Pasture. 

31 Herbaceous 72 74 97 93-100 

Rangeland. 

33 Mixed Ran~eland 52 56 93 85-100 

42 Evergreen orest 103 104 99 97-100 

Land. 

correctly interpreted, the results are as shown 

in table 10. 

TABLE 10.-Major land use and land cover cat':!gories on the 

Greeley map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

21 Cropland and 124 124 100 98-100 

Pasture. 

31 Herbaceous 72 76 95 90-100 

Rangeland. 

33 Mixed Rangeland 52 56 93 85-100 

42 Evergreen Forest 102 106 97 94-100 

Land. 

Again, these categories exceed t'le expected accuracy of 85 percent at t~e lower 

confidence limit. From the classification error 

matrix (fig. 5), it is apparent that Mixed 

Rangeland (33) is occasionally misinterpreted 

as Herbaceous Rangeland (31), while Herbaceous Rangeland (31) is misinten"''"eted as 

either Cropland and Pasture (21) or Mixed 

Rangeland (33), and Evergreen Fore::.t Land 

(42) is occasionally misinterpreted as Mixed 

Forest Land (43). These errors, few as they 

are, are the very errors expected frc'll the interpretation difficulties on this sheot. 

Atlanta 

A 1:100,000-scale land use and land cover 

map was compiled for the Greater Atlanta 

Region, Ga. The published map covered 

20,554 km2 and was centered on tho city of 

Atlanta. Part of the area of the map was initially compiled using 1:24,000-scalo orthophotoquads at that scale as a base and 

were mapped with a minimum mapping unit 

of 1 ha. The land use and land cover data 

were then generalized from the 1.:24 ,000-scale 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 ...... 

~ 42 w 

g: 43 

a: 

~51 

~ 52 0 

!:!:! 53 u. 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

4 1 

1 1 

1 

124 

1 

1 72 3 

4 1 

1 1 2 52 

2 

1 103 2 

10 

7 

2 

6 1 0 1 0 1 0 126 0 1 0 7 4 4 56 2 1 04 12 0 0 7 0 

1 

0 

1 

7 

0 0 0 0 0 0 0 1 

--f--

--f--

5 

0 

--f--

2 __ L__ 

5 0 2 

2 

0 

0 

0 

0 

1 

0 

0 

76 

5 

56 

1 0 

10 

0 

0 

7 

0 

0 

0 

0 

0 

0 

0 

0 

5 

0 

299 Correct 

413 Total 

FIGURE 5.-Ciassification matrix of the Greeley, Colo., 1 :250,000-scale land use and land cover map. For the definition 

of the numerical categories, see table 1. 

Accuracy assessment 15 
parts to 1:100,000 scale. The minimum mapPing unit for the 1:100,000 scale land use and 

land cover maps was increased from 1 ha at 

1:24,000 scale to 4 or 16 ha at 1:100,000 scale, 

according to the specifications (Loelkes 1977, 

p. 18). The remaining portion of the map was 

compiled using a stable base copy of a 

1 :100,000-scale topographic base and blackand-white high-altitude photographs at a contact scale of 1 :76,000 and at a reduced scale 

of 1:100,000. The specifications for the 

minimum mapping unit remained consistent. 

The compilers experienced the greatest difficulties in interpretation of the forest land 

categories. The black-and-white aerial photographs were obtained in February, April, and 

May 1974, and the degree of foliation varied 

with the time of photography. For this reason, 

the shades of gray on the photographs varied 

for evergreen and deciduous trees from month 

to month, so that there was no consistent signature for forest types. The interpreters had 

the greatest difficulty separating evergreen 

and deciduous forests on the May photographs, as both forest types had similar gray 

tones. This problem was as difficult to resolve 

at 1:24,000 scale as it was at 1:100,000 scale. 

These same difficulties were experienced in 

verifying the land use and land cover interpretation at the 381 sample points when the 

same photographs were used. As a result of 

these and other problems, 72 points were examined in the field. Most of these points were 

in areas of Evergreen Forest, Deciduous 

Forest, and Mixed Forest Lands. 

The number of correct interpretations for 

the Atlanta land use and land cover map at 

the 1:100,000 scale was 343 (90 percent) of 

381 points sampled as seen in the matrix (fig. 

6). The 95-percent one-tailed lower confidence 

limit is 87 percent. 

The results, obtained by a stratified systematic unalined selection of 381 points, represented the complete map at a scale of 

1:100,000. Only 13 of the 21 land use and land 

cover categories on the map appeared in the 

sample. Of the 13 categories included, only 5 

had more than 20 occurrences in the point 

selection. The results for these five categories 

examined for errors of commission are as 

shown in table 11. 

16 Accuracy of selected maps 

TABLE 11.-Major land use and land cover catCJgories on the 

Atlanta map analyzed for errors of commission 

95-percent 

Points Points Category Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 30 32 94 83-100 

21 Cropland and 86 92 93 83-100 

Pasture. 

41 Deciduous Forest 21 26 81 64- 98 

Land. 

42 Evergreen Forest 44 53 83 72-94 

Land. 

43 Mixed Forest 138 148 93 89- 98 

Land. 

Only Mixed Forest Land (43) exceeds the 

specified accuracy of 85 percent at the lower 

confidence limit. Residential (11) ard 

Cropland and Pasture (21) at 83 pert~ent for 

the lower confidence limit approact' the 

criterion of 85 percent accurate. A larger sample for all categories except for Mixed Forest 

Land would give more reliable results and 

would narrow the confidence interv~':\1. 

When these same data are examined for errors of omission the results were a~ shown in 

table 12. 

TABLE 12.-Major land use and land cover cat~gories on the 

Atlanta map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 30 32 94 83-100 

21 ·cropland and 86 92 93 87- 99 

Pasture. 

41 Deciduous Forest 21 27 78 61- 95 

Land. 

42 Evergreen Forest 44 49 90 81- 99 

Land. 

43 Mixed Forest 138 152 91 86- 96 

land. 

From these results, it appears thct the accuracies of four of these categories approach 

or exceed the criterion of 85-percent accuracy. Category 41 was less accurate, yet 

the range in accuracy was so great that it 

would be necessary to test several more 

points for more precise results. The overall 

accuracy of the land use and land cover maps 

exceeded the criterion of 85-percent accuracy 

at the scale of 1:100,000. 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 .... 

~ 42 w 

g: 43 

a: 

~51 

~ 52 c 

~53 u.. 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

30 1 1 

1 2 

3 

1 

3 1 

1 1 86 4 

3 

21 2 3 

1 44 3 

1 2 4 7 138 

5 

1 

1 

32 2 0 3 3 0 4 92 0 3 0 0 0 0 26 53 148 0 0 5 0 

1 

1 

---

--r--

1 

--r--

1-f---

1-r--

1-f---

1--

7 

32 

3 

0 

1 

0 

4 

92 

0 

3 

0 

0 

0 

0 

27 

49 

152 

0 

0 

0 

2 

0 

0 

0 

0 

0 

0 

8 

0 

0 

0 

0 

0 

0 

0000008000000 

343 Correct 

381 Total 

FIGURE e.-Classification error matrix of the Atlanta, Ga., 1:100,000-scale land use and land cover map. For the. definition of the numerical categories, see table 1. 

Accuracy assessment 17 
Seattle and Tacoma 

The Seattle and Tacoma, Wash., land use 

and land cover maps were each produced at a 

scale of 1:100,000. The area of each sheet is 

one-quarter of the standard 1:250,000 1 o x 2 o 

topographic map of the Seattle area. The 

Seattle 1:100,000-scale map includes the 

northeast corner of the standard 1 :250,000-

scale topographic map between I at 47 °30' 

and 48° N. and long 122° and 123° W. Most of 

Puget Sound and all but the southern portion 

of the city of Seattle is shown. The land area 

of the Seattle sheet is 3,326 km2 • 

Between I at 47 o and 47 °30' N. just south of 

the Seattle sheet is the Tacoma 1:100,000-

scale map. The Tacoma sheet includes the 

southern portion of Puget Sound and of the 

city of Seattle and all of the city of Tacoma. 

The land area of the Tacoma sheet is 4,110 

km2

• Both the Seattle and the Tacoma land 

use and land cover maps include major metropolitan areas, but the majority of the mapped 

area is nonurban agricultural or forest lands. 

The maps were compiled at a scale of 

1:125,000 using 1: 125,000-scale color-infrared 

high-altitude photographs acquired during 

S~ptember 1975. Once the maps were compiled, they were enlarged to a scale of 

1:100,000. The minimum mapping units for the 

1:100,000-scale maps were the same as the 

minimum mapping units as 1:250,000 scale. 

The forest categories provided the most difficulty on the Seattle and the Tacoma maps. 

This problem was further complicated by the 

presence of Western Larch, a deciduous conifer having the same signature as most evergreen trees but correctly classified as 

Deciduous Forest Land. Later, it was decided 

that this particular species would be considered correct as either Evergreen Forest (42) 

or Deciduous Forest (41) Lands. 

A total of 196 points were selected on the 

Seattle sheet and 202 points on the Tacoma 

sheet. Those points falling on boundaries 

were considered to be double points and 

thereby increased the number of points on the 

Seattle map to 212 and the number of points 

on the Tacoma sheet to 235. The land use and 

land cover interpretation was verified from the 

same photographs used for the original compilation. Only those points providing interpretation difficulties were field verified. 

18 Accuracy of selected maps 

The results were not consistent between 

the Seattle and the Tacoma map sheets. Of 

the 212 points sampled on the Sea•tle land 

use and land cover map, 206 (97 percent) were 

correct. The 95-percent one-tailed l~wer confidence limit was 95 percent. Wher the land 

area alone was considered, 162 po1nts of a 

total 168 (96 percent) were correct. The 

95-percent one-tailed lower confidence limit 

for the land area data was 93 percent, well 

above the criterion of 85 percent ac-:curate. 

For the Tacoma land use and lar1 cover 

map, 202 points (86 percent) of the total 235 

points were correct. The 95-percent one-tailed 

lower confidence limit was 82 perc·~nt. When 

the land area with the exception of category 

54 was considered, the accuracy dropped to 

83 percent or 167 correct points of the 202 

points of land-area categories. The 95-percent 

one-tailed lower confidence limit fc r the land 

area only was 78 percent, considerably below 

the accuracy criterion of 85 percent. 

Classification error matrices for Seattle and 

Tacoma are presented in figures 7 and 8. 

The major land use and land cow~r categories for Seattle analyzed for errors of commission are as shown in table 13. 

TABLE 13.-Major land use and land cover cat,;:.~ories on the 

Seattle map analyzed for errors of commission 

95-percent 

Points Category Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 47 48 98 94-100 

42 Evergreen Forest 32 33 97 89-100 

Land. 

43 Mixed Forest 43 44 98 92-100 

Land. 

54 Bays and 44 44 100 97-100 

Estuaries. 

The major land use and land cover categories for Tacoma analyzed for errors of commission are as shown in table 14. 

The primary cause of error on the Tacoma 

map sheet was misinterpretation of category 

11, as evidenced by figure 8. Six of the points 

of residential land were actually Crc~land and 

Pasture (21). Although farmsteads O" small 

clusters of buildings may have been visible on 

the photographs and in the field, su~h areas 

should not have been classified as Residential according to the mapping specifications. 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 1-

~ 42 w 

fE 43 a: 

~51 

~ 52 Q 

!:!:! 53 LL 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

47 

5 --+-- 3 --+-- 1 

2 --r-- 2 --r-- 1 1 10 --r--

--r--

--1--

--r--

--r--

--1--

--f--

9 1 --1--

32 --f--

1 1 43 --1--

--1--

1 6 --1--

0 --1--

44 --f--

--f--

2 --r--

--f--

--1--

--1--

--f--

--f--

--1--

--1--

--r--

--r--

--1--

--r--

--'----

48 6 3 1 0 2 4 1 0 0 0 0 0 0 0 9 33 44 0 6 0 44 0 2 0 0 0 0 0 0 0 0 0 0 0 0 

47 

5 

3 

0 

12 

0 

0 

0 

0 

0 

0 

10 

32 

45 

0 

0 

44 

0 

2 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

206 Correct 

212 Total 

FIGURE 7.-Ciassification error matrix of the Seattle, Wash., 1:100,000-scale land use and land cover map. For the 

definition of the numerical categories, see table 1. 

Accuracy assessment 19 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 1-

~ 42 w 

g: 43 

a: 

~51 

~ 52 0 

!:!::! 53 LL 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 74 75 76 77 81 82 83 84 85 

35 2 1 

7 1 1 

1 1 

1 

0 

1 0 

6 1 3 16 1 

4 1 

1 13 1 

1 42 4 

1 3 47 

1 

1 

33 

0 

1 1 

1 

1 

43 7 1 0 0 5 5 17 0 0 0 6 0 0 14 46 52 0 2 0 33 1 1 0 0 0 0 1 0 0 0 0 0 

38 

9 

0 

0 

27 

0 

0 

0 

0 

0 

1 

47 

51 

0 

1 

33 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

0 

202 Correct 

235 Total 

FIGURE a.-Classification error matrix of the Tacoma, Wash., 1:100,000-scale land use and land cover map. For the 

definition of the numerical categories, see table 1. 

20 Accuracy of selected maps 
TABLE 14.-Major land use and land cover categories on the 

Tacoma map analyzed for errors of commission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 35 43 81 68- 94 

42 Evergreen Forest 42 46 91 82-100 

Land. 

43 Mixed Forest 47 52 90 81- 99 

Land. 

54 Bays and 33 33 100 96-100 

Estuaries. 

Those categories of forest land believed to 

cause difficulties for the interpreter were actually mapped with a high degree of accuracy. 

From figures 7 and 8, it was possible to 

determine the errors of omission. Major land 

use and land cover categories of Seattle expressed in terms of errors of omission are as 

shown in table 15. 

TABLE 15.-Major land use and land cover categories on the 

Seattle map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 47 47 100 96-100 

42 Evergreen Forest 32 32 100 95-100 

Land. 

43 Mixed Forest 43 45 96 87-100 

Land. 

54 Bays and 44 44 100 96-100 

Estuaries. 

The major land use and land cover categories of Tacoma expressed in terms of errors 

of omission are as shown in table 16. 

TABLE 16.-Major land use and land cover categories on the 

Tacoma map analyzed for errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 35 38 92 82-100 

21 Cropland and 16 27 59 39- 79 

Pasture. 

42 Evergreen Forest 42 47 89 79- 99 

Land. 

43 Mixed Forest 47 51 92 84-100 

Land. 

54 Bays and 33 33 100 95-100 

Estuaries. 

The most obvious difference in the data for 

errors of omission and the data for errors of 

commission was on the Tacoma sheet. Cropland and Pasture (21) on the Tacoma map 

sheet was often overlooked. Much of tile 

Cropland and Pasture land was misclaf~ified 

as Residential (11) or Other Urban and BuiltUp Land (17) resulting in large errors of commission for Residential Land and large errors 

of omission for Cropland and Pasture. rhould 

these errors be corrected, Cropland and 

Pasture would become a more significc'lt 

category on this map sheet. 

Combined Results 

When all the point data for these ma..,s 

were merged, a combined classification error 

matrix was constructed as shown in fi~··Jre 9. 

A sufficient number of points was accumulated to provide a reliable estimate of t1e interpretability of nine categories. Reside:'ltial 

(11 ), Cropland and Pasture (21 ), Herbaceous 

Rangeland (31), Mixed Rangeland (33), Deciduous Forest Land (41), Evergreen Forest Land 

(42), Mixed Forest Land (43), Lakes (52), and 

Bays and Estuaries (54) were all 85-perc.ent 

accurate or better at the lower confidence 

limit when tested for errors of commisf 1on. 

Only Residential (11) was less accurate at the 

lower confidence limits. The p values calculated from errors of commission for these 

categories where p is estimated at ± 10 percent of its true value are shown in tablo 17. 

TABLE 17.-Accuracy of combined data: errors of 

commission 

95 oercent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 177 204 87 8?.- 92 

21 Cropland and 354 373 95 93- 97 

Pasture. 

31 Herbaceous 172 181 95 9?.- 98 

Rangeland. 33 Mixed Rangeland 52 56 93 8':':·-100 

41 Deciduous Forest 280 297 94 91- 97 

Land. 

42 Evergreen Forest 318 348 91 A8-94 

Land. 

43 Mixed Forest 565 608 93 91- 95 

Land. 52 Lakes ______ 25 26 96 87-100 

54 Bays and 150 150 100 s~-1oo 

Estuaries. 

For comparison, these same categories 

calculated from errors of omission are shown 

below in table 18. 

Combined results 21 
11 

12 

13 

14 

15 

16 

17 

21 

22 

23 

24 

31 

32 

z 33 

Q 41 1-

~ 42 w 

g: 43 

0: 

~51 

~ 52 0 

!±:!53 

u.. 

a: 54 w 

> 61 

62 

71 

72 

73 

74 

75 

76 

77 

81 

82 

83 

84 

85 

ORIGINAL INTERPRETATION 

11 12 13 14 15 16 17 21 22 23 24 31 32 33 41 42 43 51 52 53 54 61 62 71 72 73 7 4 75 76 77 81 f? 83 84 85 

177 3 2 3 1 1 1 

1 22 1 2 2 1 1 1 

1 7 1 

15 1 

1 

2 

1 12 1 1 

10 1 1 4 354 3 3 4 3 

2 1 17 1 

4 

1 2 172 3 1 1 

4 1 1 

1 1 2 52 

1 5 1 280 4 25 1 1 

4 1 1 318 13 1 

5 1 2 12 23 565 

5 

1 25 2 

1 13 

150 1 

1 1 1 1 35 1 1 

1 2 7 

1 

3 

2 1 1 27 

1 

7 

5 

2 

204 25 8 15 3 9 2137317 5 1 181 4 56 297348608 5 26 15150 42 9 0 1 0 5 31 0 7 5 0 2 

188 

31 

9 

16 

15 

383 

21 

4 

0 

180 

6 

56 

318 

338 

608 

5 

28 

14 

1 51 

41 

10 

0 

0 

0 

3 

31 

0 

5 

0 

2282 Correct 

2475 Total 

FIGURE 9.-Ciassification error matrix of the combined results. For the definition of the numerical categories, see 

table 1. 

22 Accuracy of selected maps 
TABLE 18.-Accuracy of combined data: errors of omission 

95-percent 

Category Points Points Percent confidence 

correct total correct limits 

(percentage) 

11 Residential _____ 177 188 94 90- 98 

21 Cropland and 354 383 92 89- 94 

Pasture. 

31 Herbaceous 172 180 96 92- 99 

Rangeland. 

33 Mixed Ran~eland 52 56 93 85-100 

41 Deciduous orest 280 318 88 84- 92 

Land. 

42 Evergreen Forest 318 338 94 91-97 

Land. 

43 Mixed Forest 565 608 93 91- 95 

Land. 52 Lakes ______ 25 28 89 76-100 

54 Bays and - 150 151 99 97-100 

Estuaries. 

Both Deciduous Forest Land and Lakes 

were less than 85-percent accurate at the 

95-percent lower confidence limits. However, 

the value for Deciduous Forest Land is calculated to be 84.33 which is acceptable as a 

lower confidence limit. Lakes, on the other 

hand, had too wide a confidence interval to 

be a reliable estimate of the accuracy. A 

larger sample of Lakes would be necessary 

for a reliable comparison of the errors of commission and of omission. 

The accuracy for all points combined was 

92 percent or 2,282 points of a total of 2,475 

points with a 95-percent lower one-tailed confidence limit of 91 percent. 

Conclusions 

The selected land use and land cover maps 

interpreted from high-altitude photographs 

meet the criterion that they be mapped with 

an accuracy of 85 percent. Table 19 is a summary of these results. The single exception to 

this for those maps tested was the Tacoma, 

Wash., map sheet where the accuracy was 

less than 85 percent at the lower confidence 

limit. Those categories causing interpretation 

difficulties were not the same on all map 

sheets, and the number of errors were not 

always the highest for these categories. 

Errors committed in general were predictable 

errors between categories of similar signatures or within a Level I category. Categories 

in error for the most part were found to fall 

within the predictable error types shown in 

figure 1. Each user must judge the seriousness of any of these error types for his r~eds. 

TABLE 19.-Land use and land cover map accura-::ies for 

selected maps 

9::--oercent 

o'1e·tailed 

lower 

Map sheet Scale Points Points Percent confi· 

correct selected correct dence 

limit 

(percent· 

age) 

Tampa ____ 1:250,000 329 354 93 91 

Portland __ 1:250,000 410 456 90 87 

Charleston_ 1 :250,000 393 424 93 90 

Greeley ___ 1:250,000 399 413 97 95 

Atlanta ___ 1 :100,000 343 381 90 87 

Seattle ____ 1:100,000 206 212 97 95 

Tacoma ___ 1:100,000 202 235 86 82 

When all points sampled for these rna p 

sheets were combined, the results yielded 

sufficient points to provide reliable results for 

nine categories. All categories sampled with a 

significant number of points exceed the required accuracy of 85 percent. Only one category on the maps, Residential (11), was less 

than 85-percent accurate at the lower confidence limit. Although the sample value exceeds 85 percent, the lower confidence limit 

is 82 percent, indicating there may be P"Oblems in mapping that category. The errc rs of 

overestimating Residential would be a s-~rious 

disadvantage to may users, and so extra caution should be employed when mapping this 

category. 

Although the lower confidence limit i~ the 

lowest value accepted (with 95-percent confidence) as the true accuracy of the map, 

there is just as much chance that the maps 

exceed the measured accuracy as fall st,ort of 

it. The lower confidence limit, therefore, is a 

conservative estimate of whether the maps 

meet the accuracy criteria of 85 percent. 

Those categories whose sample results fall 

short of 85-percent accuracy at the lower confidence limit may still meet or exceed 

85-percent accuracy in the true population. 

A more precise accuracy statement w0uld 

be possible if all categories on the map were 

sampled with a sufficient number of points to 

be analyzed reliably with a narrow confidence 

interval, a procedure which would require a 

Conclusions 23 
presample knowledge of all categories on the 

map. Such a sampling technique, using 

digitized land use data, is being developed at 

the Survey to sample an optimum number of 

points for each category. 

References 

Anderson, J. R., Hardy, E. E., Roach, J. T., and Witmer, R. 

E., 1976, A land use and land cover classification system for use with remote sensor data: U.S. Geological 

Survey Professional Paper 964, 28 p. 

Berry, B. J. L., and Baker, A. M., 1968, Geographic sampling, in Berry, B. J. L., Brian, J. L., and Marble, D. F., 

24 Accuracy of selected maps 

eds., Spatial analyses-a reader in statis•ical geography: Englewood Cliffs, N. J., Prentice Hall, p. 

91-100. 

Fitzpatrick-Lins, Katherine, 1978, Accuracy of selected 

land use and land cover maps in the GreRter Atlanta 

Region, Georgia: U.S. Geological Survey ,Journal of 

Research, v. 6, no. 2, p. 169-173. 

Genderen, J. L. van, and Lock, B. F., 1977, Testing landuse map accuracy: Photogrammetric Eng''leering and 

Remote Sensing, v. 43, no. 9, p. 1135-1137. 

Loelkes, G. L., Jr., 1977, Specifications for l.!ind use and 

land cover and associated maps: U.S. Ge·.,logical 

Survey Open-File Report No. 77-555, 115 p. 

Snedecor, G. W., and Cochran, W. F., 1967, Statistical 

methods: Ames, Iowa State University PrE'ss, p. 

202-211, 516, and 517. 

-k U.S. GOVERNMENT PRINTING OFFICE: 1980 0-311-3«'186