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Proceedings, XXth congress

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004

(Table 4) The resulted correlation coefficients of the field data
with image data

Vegetation Correlation Vegetation Correlation
Hidex or coefficient Indeseot coefficient
Band Band
IR2 0.19 B3FU -0.087
MIR 0.184 B4 0.147
MND 0.329% B4FU 0.018
MSI 0.111 B5 0.154
NDVI 0:320* B5FU -0.053
NIR 0.322% B6L -0.044
RA 0.127 B6LFU -0.006
SAVI 0.329% B6H -0.200
TVI 0.329* B6HFU 0.003
IRI -0.092 B7 0.112
VNIRI 0.302 B7FU -0.242
VNIR2 0.335* B8 -0.038
PD311 -0.135 HYB2 -0.214
PD312 -0.130 HYB3 -0.234
PD321 -0.80 HYB4 (:38]**
PD322 -0.034 VII 0.150
MIRVI 0.309* VI2 -0.148
MIRV2 0.352* VI3 -0.392**
MINI 0.019 VIA -0.270**
BI -0.114 VIS -0.027
BIFU 0.184 VI6 -0.055
B2 -0.147 VI7 -0.069
B2FU -0.012
B3 -0.132

* Significantly at P=5% and ** significantly at P=1%
FU= fused band using HIS method
HYB- fused band using spectral response method
The results of stepwise regression analysis are shown in Table
(4). On the basis of this table contents, it is possible to create a
model to predict the percentage cover over the whole studied
Table -4- Results of step wise regression analysis

R? Mean of Degree of Source of Variable
Squares freedom Variation
Regression NIS
1256.03 4 B7FU
0.64 Enter HYB4
80.71 35 B5FU

The suggested model is:
Y= percentage cover,
B6H= band 6 high gain,
BSFU= fused band 5 using HIS method ,
B7FU= fused band 7 using HIS method
HYB4= fused band 4 using spectral response method
Sepehri (2000) applied the mentioned vegetation indices in
Jahannema area, Gorgan, Iran and also Boyd et al (1996) and
Sepehri et al (1998) used these indices as well. They expressed
since there are high variations among cover data, so the
vegetation indices are not much applicable to asses the
vegetation cover. Among the examined indices, VI3 has highest
correlation coefficient with vegetation cover (r=39.2%). Also
the Sepehri et al (1998) and Boyd et al (1996), researches have
reched the similar results. And the same results have been
discussed for the VI6 vegetation index. NDVI has positive
correlation with vegetation cover because of the high spectral
reflectance of vegetation cover in band 4. Khajeddin in 1995
has proved that NDVI is one of the indices that have correlation
with vegetation cover at Jazmourian area. The low correlation
coefficient between NDVI and vegetation cover is due to soil
back ground (Apan et al 19997). MIRV2 has a high correlation
with vegetation cover (r=35%). It seems that, the high
vegetation reflectance on near infrared region is responsible to
this point. Hyb4, created from merging panchromatic band with
band 4, 3 and 2 data, has correlation with vegetation cover
(P=1%). Considering the fusion algorithm in spectral responses,
the spectral reflectance of Hyb4 is very similar to band 4. In
addition, the latter spectral region of the vegetation reflectance
is considerable; therefore this band could be used frequently to
estimate vegetation cover.
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Klonzak, M., 1996. An assessment of radiance in landsat TM
middle and thermal infrared warebands for the detection of
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Khalilpour S.A., 2004. Utilizing vegetation indices, first and
fused bands for vegetation cover percentage mapping, National
Geomatics conference, lanian National Cartographic Center.
5- Khajeddin, S.J., 1995. A survey of the plant comunities of
the Jazmorian, IRAN, using Landsat MSS data. Ph. D. thesis
University of Reading
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in environment, a case study in the Caucau region of Colombia,
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