Geoscience Reference
In-Depth Information
Table 14.2
Producer's and User's Accuracies by Land-Cover Type (
Continued
)
Producer's
Accuracy
(%)
User's
Accuracy
(%)
No. of
Sites
Standard
Error
Standard
Error
Code
Cover Type
44
Great Basin Big Sagebrush-Juniper-
Pinyon
30
20.0
6.5
13.3
5.5
45
Great Basin Sagebrush-Mixed
Grass-Mixed Scrub
27
20.0
7.0
22.2
7.3
46
Great Basin Shadscale-Mixed
Grass-Mixed Scrub
24
0.0
0.0
0.0
0.0
47
Great Basin Greasewood Scrub
11
37.5
14.8
27.3
13.6
48
Great Basin Saltbush Scrub
7
6.7
9.5
14.3
12.9
49
Great Basin Blackbrush-Mixed Scrub
36
16.0
5.8
11.1
5.0
50
Great Basin Mormon Tea-Mixed
Scrub
18
19.4
9.1
33.3
10.9
51
Great Basin Winterfat-Mixed Scrub
11
0.0
0.0
0.0
0.0
52
Great Basin Mixed Scrub
26
9.1
5.6
11.5
6.3
53
Great Basin Mormon Tea/Pinyon-
Juniper
16
0.0
0.0
0.0
0.0
55
Mohave Creosotebush-Bursage
Mixed Scrub
7
28.6
17.9
28.6
17.9
58
Mohave Blackbush-Yucca Scrub
13
50.0
10.4
23.1
8.7
59
Mohave Saltbush Yucca Scrub
5
0.0
0.0
0.0
0.0
61
Mohave Creosotebush-Brittlebush
Mohave Globemallow Scrub
5
0.0
0.0
0.0
0.0
63
Mohave Joshua Tree
1
0.0
0.0
0.0
0.0
64
Mohave Mixed Scrub
9
9.1
9.8
11.1
10.7
75
Sonoran Paloverde-Mixed Cacti-
Mixed Scrub
1
0.0
0.0
0.0
0.0
82
Agriculture
1
0.0
0.0
0.0
0.0
83
Urban
11
41.7
14.9
90.9
8.6
84
Industrial
7
60.0
18.9
85.7
13.4
85
Mixed Agriculture/Urban/Industrial
20
80.0
7.7
20.0
7.7
87
Water
2
0.0
0.0
0.0
0.0
“absolutely right.” Instead, they range from a minimum of 1.039 to a maximum of 4.934, and mean
and median are very close to 3.0 (Figure 14.5).
The fuzzy spatial view of accuracy displays the predicted accuracy ranks reclassified as an
ordinal variable (Figure 14.6). High accuracy is lighter in color than low accuracy. The frequency
histogram of accuracy ranks shows that approximately 85% of the fuzzy spatial view of accuracy
had a rank of 3, 4, or 5 (Figure 14.5). In ecological terms, the LC map was accurate to the life
form level or better for a majority of the study area.
14.5 DISCUSSION
A binary analysis using an error matrix provides limited information about thematic accuracy
of a LC map. In fact, an overall accuracy of 14.8% for the map was dismal and discourages use
of the map for any application. However, this was not unexpected given the preliminary nature of
the map, high number of cover types, small reference data sample size (
) compared to the number
of cover types and lack of documentation of the Graham vegetation types. In fact, a binary analysis
is conservatively biased against a classification system that is poorly defined and numerous in
classes (Verbyla and Hammond, 1995). The lack of descriptions in the Graham classification system
made labeling the cover type of each reference point difficult. In addition, division of the cover
types of Arizona into 105 classes made distinguishing between types problematic. Therefore, a
binary analysis likely assigned a wrong answer to locations with partially correct LC classification.
n
