As the next figures and next paragraphs show the mixed
pixels are classified wrongly using different classification
rules.
The criteria of the first classification are the following
ones:
- supervised classification;
- bands: all the recorded channels
- maximum likelihood method;
- . threshold: 596
- classes: snow, green, vegetation, water, cultivated
field, rice-field, cloud.
The next figure 4 shows the entire classified image: in
white the blanket of snow.
Me Wa m = 20 Ww Cr in à T eel “iles
= a M A, Fre hia N von IB dme d .
x, Fl, a } At t > es x * Eee 2
zy $e SE 9^ . -
enr - ate : , = rw us
: be uL. > m 1 > ete Yo
‘ ur 2 ut iy P
die s ; > ied SNS TE TRE à
un J x net ae RE I X wm rt “2
RE tye aa GSP SAT Vut e cam LAT
à NES -— am cmt "NA unir
A ROC S Pr E
m ME p. Bag nod -— :
: FARBE Ar eS tem ti
- ; a N us "o 2
= << . » P set 4 un.
ate al BEY ee Ti
al pt í ad.
ie oos
AE AE s ma ci
Figure 4: the result of first classification.
Figure 5 shows that the borderlines around snow layer,
where many pixels are likely to be mixed, are classified as
clouds. That day the weather was sunny and so it is easy
to understand that the pixels classified as clouds along
the borderlines are not reaily clouds but they are snow
added to green and we can really say that this
classification assigns part of the mixed pixels to an
extraneous class (error Ill).
M t ry»
i ow EA, ; A
m I x ; A
-— & - i a » Et ee
33 wry WW - t e
^i . * A, f.
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; # E * Ss now” és ; Le M
- $ E 1 i N s je 3
t ^ i a * 4 1
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x ^ 3 - 4 is » Ber 217. P9",
Sols pty wm is pu 4 au. ;
(x AA .Aa 58 (l5
4&á nonsnow 1:53 *.,
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e opu T. i eh.
wiper - p^ E 3 £C e "ol >
Aum Fa Fra, gn ce ms
Meet wt uit a S ei w^ x
ky aE, ^ a =
WG cm d (E
Sai ein Y sett
y bw
Figure 5: a zoom into the image 4. The borderline around
the snow areas is classified as cloud (dark grey)
In order to give different weight to thermal information
contained in the channels 4 and 5, the same classification
criteria are performed only with tree channels (1, 4 and 5).
The criteria of the second classification are the following
ones:
- Supervised classification;
- bands: channels 1, 4 and 5;
- | maximum likelihood method;
- . threshold: 596;
- classes: snow, green, vegetation, water, cultivated-
field, rice-field, cloud.
Figure 6 shows the results of the second classification.
Figure 6: a zoom into the second classified image. The
borderline around the snow areas is still classified as
clouds (dark grey).
Comparing figure 5 and figure 6 we can observe that they
both assign snow-green mixed pixels to an extraneous
class.
A third new classification is done whit only one thermal-IR
channel:
- supervised classification;
- . bands: channels 1 and 5;
- maximum likelihood method;
- . threshold: 596
- classes: snow, green, vegetation, water, cultivated
field, rice-field, cloud.
In Figure 7 the results of the third classification are shown.
AN LA Te "e le. duh aa
5 STE e Uum
S M BO i - =
+ Br
*
A^ bm.
re ae
Figure 7: a zoom into the third classified image. The
borderline around the snow areas is still classified as
cloud (dark grey)
Even using only one thermal band (channel 5) the snow-
green mixed pixels are classified as cloud.
5. THE SPECTRAL SIGNATURES
In order to understand the behaviour of snow-green mixed
pixels their spectral signatures are compared together and
with the clouds one.
Figures 8, 9 and 10 show the characteristic spectral
signatures .
330 International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 7, Budapest, 1998
Figure
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