2004 ; ; x 
LE International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
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E 
Class in 91 Class in changes Number Area changes 
98 of pixel (ha) 
No Forest No N-F--->N-F 990727 80471.80 
Forest 
No Forest Low N-F--->[-F 88894 7220.41 
vegend | Forest 
Dens Forest No Forest Middle N-F--->M-F 71510 5808.39 
[___]Low-Forest Forest 
A Es [__|Middle-Forest No Forest Dense N-F---2D- 20101 1632.70 
| PRÉ. e n [FE ]NO-Forest Fare 
aided s AE M water orest 
; ; Low. Forest NO HE Í 2310 | 
Figure7. Forest canopy density map 1991 . BATSI 
Low Forest Low L-F---»L-F 4703( 3820.01 
Forest 
'orest Low Forest Middle [-F--->M-F 231031 18765.49 
"Ores E 
we Forest 
orest 
-Forest Low Forest Dense L-F--->D-F 14701 1194.08 
rest Forest 
Middle NO M-E----N-I 165575 
Forest Forest 
Middle Low M-F---L-l 68828 3590.5 
y and Forest Forest 
Middle Middle M-F--->M-F 223747 1817385 
Forest Forest 
[ Legend Middle Dense M-F--->D-F 126746 10294 94 
| Mens Forest Forest Forest 
J.A 
à [. ]Low-Forest Dens x SE KT OÓDAO0 
%) | Lu a al } [__]Middie-Forest i/eHse Ny DEAN Used 
36 iris Em rimi ass + = NO-Forest FOTOS Forest 
Fz ue" Eo cJ) N water Dense Low D-F---»L-I 
9 | [Forest Forest 
^ . Yona Midale PYF is Make 136825 FEEL 
22 Figure 8. Forest canopy density map 1998 Lense Mas DEM ae Ais 
Forest Forest 
3.01 ; : : ec | Dense Dense D-F--->D-F 10932 9492.5( 
Pixel size at both dates is 28.5 m. Forest Forest 609326 fon 
"Ores ‘Ores 
Since every map has 5 classes, 25 different case will happen Table 3. The rate of forest canopy density changes during 91-98 
in the changes map. 9 cases don't relative to the forest class 
T . . ~ ^h: es c1 5195 a (59 3994 
changes. Totally, we will have 16 different cases for the NO Changes 5131938 13439,5090) 
forest changes, that the map below shows the forest canopy : 
i Deforested =59005 ha (23.06%) 
density changes at the two dates. 
Growing = 44916 ha (17.55%) 
] site 7. CONCLUSIONS 
Legend % : : . 
M-F*N-F (NO Change) Conventional RS methodology, as generally applied in 
at d (INF *L-F (growing) forestry is based on qualitative analysis of information 
MN Eur growing) derived from “training areas” (i.e. ground-truth). This h: 
d be EC IN-F *0-F (growing) erived from "training areas" (i.e. ground-truth). This has 
doe LF * N-F (de'orestaticn) certain disadvantages in terms of the time and cost required 
mage, [. ]tF *t-F (NO Change} for training area establisl t. as well as to ensure a hiel 
They [IL * MF (growing) or training area establishment, as well as to ensure a high 
pared [ES]L-F * D-F (growing) accuracy. Unlike the conventional qualitative method, the 
pe []M-F * N-F. (deforestaton) ^ : 712 ; . > P farodfe 
1d 98. vie aden FCD model indicates the growth phenomena of forests by 
[.— ]m-F * M-F (NO Change) means of qualitative analysis. The accuracy of methodology 
-F*D- Wi > : = + ; 
Le is checked in field test. The case of Iran, the correlation 
D-F*N-F (deforestation) TE ; i 
[_Jo-F* LF (deforestation) coefficient value between FCD model and field check shows 
Ex mr tm 0.83. It indicates higher correlation and accuracy compared 
™ = to conventional remote sensing method. FCD model is very 
Figure 9. Forest canopy density changes during 91&98 useful for monitoring and management with less ground truth 
survey. 
The table 3 shows the rate of these changes. 
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