verall | 
Kappa 
0.46 
060 | 
  
  
  
y Site 
lata set (Ahl, 
)y examining 
ere evaluated 
iyers was the 
. They were 
Similarly to 
> four groups 
1Omogeneous 
ISer accuracy 
Kappa were 
st among all 
0 study site 
. Orono by 
r agreement. 
grated mod! 
phasizes the 
> aggregation 
pected result 
ce ratio. The 
and Kapp 
able 1). This 
nfluenced by 
est of Kappa 
es when tle 
he integrated 
ents on bof 
| significant 
5.0 CONCLUSIONS 
The integrated model provided a flexible and promising 
approach for the mapping of forested wetlands from satellite and 
ancillary data (hydric soil. slope, NWI maps. hydrology). The 
formulated algorithm can be extended through a GIS expert 
svstem for an automated classification approach. However, the 
ancillary data set needs to be investigated further to broaden the 
consideration of GIS layers. For example, the slope layer may 
need to be referenced to terrain positions or shape because 
forested wetlands are less likely to occur on convex shape slopes 
and ridge topographic positions, and are more likely to occur on 
concave, flat terrain. Skidmore's (1989) topographic position 
model of ridge, side slope, toe slope, bottom was reviewed but a 
suitable program was not available to this study. The poor 
contribution of the stream buffer layer suggested that this 
variable can be ignored or possibly combined with a topographic 
variable. This investigation and Ahl's (1994) work suggest that a 
hybrid classification and the integrated GIS model are the most 
promising for identification and mapping of forested wetlands. 
On the basis of the two Maine study sites and the variables tested 
the level of effort to develop and implement a forested wetland 
mapping model does not appear to be justified over the 
conventional hybrid classification approach. Furthermore, the 
satellite and GIS methods may not be an improvement over NWI 
(aerial photo methods) for mapping forested wetlands in Maine. 
However, the satellite mapping approach can provide more 
complete inventory of land cover types than is available from 
> 
Table 2 Analysis Matrix of the Integrated Model with Weighted GIS Layers: 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Acadıa Study Site 
Integrated Model Analysis Matrix 
of Weighted GIS Layers 
H|S|N|B F Combi Aerial Photo Sample Plots 
Y|L|W|U S nation Forested Other Forested Other Assigned 
SIPIIIÓIT T Level Wetland Wetland Upland Upland Total Categories 
0 [0:40:40 0 0 6 35 112 385 538 Other 
01:01 0 d 0 1 0 0 0 0 0 Upland 
0 10} 2} 0 0 2 0 8 15 15 38 
0102/1 0 3 0 0 0 0 0 
074 | 0:| 09 0 4 6 23 18 75 122 
014 |9]7 0 5 3 6 3 9 23 
0141210 0 6 4 7 0 0 11 
Q442 | 0 7 0 0 0 0 0 
21010190 0 8 11 10 10 0 31 
8707011 0 9 1 7 2 0 10 Other 
$191 219 0 10 0 1 0 1 Wetland 
$101.21 1 0 11 0 0 0 0 0 
814109010 0 12 12 18 12 18 60 
$1401 0 13 ] 19 0 0 20 
8141270 0 14 5 15 0 0 20 
1412] 1 0 15 0 0 0 0 0 
0101060 16 16 85 26 1153 120 1384 
ÿ 10 P604-1 16 17 6 9 112 3 130 
9101210 16 18 4 0 1 0 5 
910/211 16 19 0 0 0 0 0 Forested 
0147010 16 20 49 9 209 18 285 Upland 
014101 16 21 9 1 20 3 33 
01412 10! 16 22 10 0 4 2 16 
8144211 16 23 0 0 0 0 0 
810} 010 16 24 117 9 155 ] 282 
8101011 16 25 ...18 4 36 0 58 Forested 
819]2. 01 16 26 5 0 3 0 8 Wetland 
850[2]1-1. ig 27 4 0 2 0 6 
[$ 41010 16 28 167 11 56 17 251 
214 /01 1) 16 29 20 8 7 0 35 
131342 [0] 46 30 54 9 4 0 67 
En $12 11 16 31 4 0 0 0 4 
Total 603 234 1935 666 3438 
Threshold Control by 408/603 113/234 1475/1935 385/666 
Balance Ratio 0.68 0.48 0.76 0.58 
423 
International Archives of Photogrammetry and Remote Sensing. Vol 
. XXXI, Part B7. Vienna 1996