ion quality in 
ansmitting and 
n performance 
and reliability. 
certainty of the 
y, as a special 
ertainty of the 
(fuzziness) for 
s (IF) can be 
(5) 
tainty) to 1.0 
s may allow 
rich can either 
utputs) or the 
assan 2006). 
was Landsat-7 
d Fab'9, 2001) 
Itispectral data 
| (0.525-0.605 
).90 um), mid 
.09-2.35 um)) 
d as Rann of 
2’-70°33’E) in 
n. To separate 
r bodies with 
Long 70?05'E- 
one class that 
in mind, the 
re. 
spectral - 
| ratio 
ntional | 
al band — 
io 1]: 
multispectral 
all band ratio 
ly, an attempt 
ratio temporal 
indices from 
equation (1), applied on study area to identify liquefaction. The 
noise classifier was applied as supervised classifier to extract 
single class, liquefaction as well as water bodies separately. 
Finally the accuracy assessment through entropy analysis using 
equation (5) was done for both liquefaction and water bodies. 
4. RESULTS AND DISCUSSION 
This study mainly focuses on identifying the areas in and 
around Kachchh region with abnormal increase in liquefaction 
after the Bhuj earthquake in 2001. The basic principle behind 
using the satellite images in mapping the liquefaction changes 
is that electromagnetic spectrum absorbed by liquefied soil for 
different indices is different. Different indices help to 
distinguish reflectance of soils by its moisture content. The one 
class of interest, namely, liquefaction was studied for 
discrimination with background and especially separates it with 
water bodies in the study area. 
  
  
  
  
  
  
  
  
  
  
  
  
  
For liquefaction identification 
5 2 ^ 
= 9 9 2. 
& = = BE > 
nt So Eo 30 £ 
E a — gg. 2 
e es eg =| - 
e «> eT e E » = 
E a 9 = 3 m 
o - Ex E 
e" oo e 
CBSI- 0 0.847 0.901 0.039 
NDVI 
CBSI-SAVI 0 0.843 0.929 0.028 
CBSI-SR 0.020 0.023 0.964 0.028 
CBSI- 0 0.960 0.968 0.011 
TNDVI 
Conv.-SR 0.262 0.223 0.988 0.028 
Conv.- 0 - 0.667 0.917 0.183 
MNDWI 
  
  
Table 1. Temporal indices results for liquefaction identification 
  
  
  
  
  
  
  
  
  
  
  
  
  
> For water body identification 
9 wu N 
= 9 3 2 
= = = SE > 
= = o = o = v o Du 
Em -- = T = E o = 2 
2. = 3 e$ EES | EB 
E 5 9 > 2 = 
o > E g 
fu o6 e 
CBSI- 0.639 0.796 0.933 0.056 
NDVI 
CBSI-SAVI 0.639 0.792 0.894 0.022 
CBSI-SR 0.039 0.031 0.980 0.011 
CBSI- 0.905 0.949 0.960 0.005 
TNDVI 
Conv.-SR 0.564 0.482 0.921 0.022 
Conv.- 0.603 0.741 0.913 0.044 
MNDWI 
  
  
Table 2. Temporal indices results for water body identification 
The NDVI, SAVI, SR and TNDVI band ratio techniques were 
applied on both images using CBSI spectral band ratio 
approach, while SR and MNDWI were used conventional 
method to find out liquefaction as well as water bodies. The 
region behind it is CBSI-MNDWI behaves like CBSI-NDVI; 
and conventional NDVI, SAVI and TNDVI gives negative 
values for liquefaction identification. Only SR technique was 
used as CBSI as well as conventional approach because it use 
direct ratios between band 3 and band 7, and ratios between 
band 3 and band 4 respectively. 
  
onventional 
-SR i 
  
d © Liquefaction 
1 
  
  
Q0 «—— —— ——— Value of u 
p= Membership Value 
Figure 2. Different classified output for liquefaction 
identification 
It was observed from table 1 for liquefaction identification, the 
temporal indices values of CBSI-SR and conventional SR 
shows higher correlation and CBSI-TNDVI shows least 
correlation. The CBSI-TNDVI shows least entropy (0.011) for 
liquefaction identification. As water bodies not changed in this 
period (Jan'8, 2001 and Fab'9, 2001) therefore the temporal 
indices values for water bodies not changed very much. For 
water bodies identification it is observed from table 2 that all 
temporal indices shows good results but CBSI-TNDVI shows 
least entropy (0.005). The classified outputs are shown in 
figures 1 and 2 for identifying liquefaction as well as water 
bodies respectively. 
5. CONCLUSION 
In this study, effect of different indices (CBSI and 
conventional) has been studied for extracting liquefaction as 
well as water bodies in the study area. From table 1, it was 
observed that temporal indices from NDVI, SAVI and TNDVI 
using CBSI method and conventional MNDWI show less 
correlation for liquefaction, implying these are outperform to 
identifying liquefaction. The results indicate from classified 
output and temporal indices values that CBSI-TNDVI is best 
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