| ALd © 
Pr ESUN,,.cos6, 
Where, 
py Unitless planetary reflectance 
L , = Spectral radiance at the sensor's aperture 
d = Earth-Sun distance in astronomical units from 
nautical handbook 
ESUN 4" Mean solar Exoatmospheric irradiances 
0. = Solar zenith angle in degrees 
iii) Estimation of NDVI: Normalized Difference Vegetation 
Index (NDVI) was estimated using the following equation 
(Hansen et al, 2000): 
NDVI = (NIR - Red) (7) 
(NIR + Red) 
Where, 
NIR: Near Infra-Red band 
Red: Red band 
For Landsat TM and Landsat ETM+ and ALOS AVNIR-2, 
band 3 is Red and band 4 is NIR. 
3.2.2 Separating Vegetation and Non-vegetation Area: 
NDVI threshold was used for grossly separation of vegetation 
vs. non-vegetation areas. Furthermore, threshold to NDVI and 
then to band 3 brightness was applied to divide vegetation area 
into two; named as ‘Vegetation A’, and ‘Vegetation B’. This 
was useful for separating relatively dense forest land (that is, 
Forest (Closed)) which was found synchronized under 
‘Vegetation A’. 
Landsat ETM+ had no haze and hence for this image, water 
body was separated from non-vegetation area at this step using 
threshold to NDVI Threshold followed by some editing. The 
non-vegetation excluding water body was named as ‘Other 
Non-vegetation’ area. 
3.2.3 Unsupervised Classification: The Optical TOA 
reflectance image was then clipped separately with the 
‘Vegetation A’, ‘Vegetation B’ and ‘Other Non-vegetation’ 
area boundary. These clipped images were run for unsupervised 
classification with 20 classes and employing all 4 bands for 
ALOS AVNIR-2 and all bands except band 6 for Landsat TM 
and Landsat ETM+. 
3.2.4 Recoding and compiling LC Classes: After careful 
interpretation of the above yielded classes, these recoded to the 
appropriate class and then combined together. Lastly, manual 
editing was carried out wherever necessary. Settlements were 
found more intermingle with other LC classes, relatively more 
manual editing was required to extract this LC class. 
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
3.3 Accuracy Assessment of LC Results and Change 
Analysis 
Accuracy assessment was carried out for LC result from the 
latest satellite data, ALOS AVNIR-2 employing the field 
experience and secondary information. For this, checking was 
done for 230 selected points (pixels), which were randomly 
selected throughout the scene 
LC change analysis was carried out by overlaying the LC result 
all three epochs. For comparison purpose, the LC result from 
ALOS AVNIR-2 was resampled to 30m in order to match with 
other two epochs (Landsat TM and ETM+). Altogether 242 
pixels were tracked for change. 
4. RESULTS AND DISCUSSION 
4.1 Cloud/Shadow and Haze Identification and Removal 
As presented in Figure 4, the result of cloud/shadow and haze 
removal for ALOS AVNIR-2 has remained very promising. The 
result of removing cloud in Landsat 7 ETM+ was also good, 
however, some of the pixels were found mis-replaced which 
might be because of the wider gap between acquisition date of 
Landsat 7 ETM+ and ALOS PALSAR. 
The haze removal algorithm also worked well and it removed 
haze from all 3 bands; Blue, Green Red (that is, < 800nm). 
Haze appears in these bands (Richter, 2011). 
  
Dehazed Image 
     
  
ALOS AVNIR-2 4,3,2) 
original image 
3 Cloud, Shadow, and 
  
  
  
Figure 4. ALOS AVNIR-2 Cloud/Shadow & Haze Removal 
a) ALOS AVNIR-2 with Cloud/Shadow & Haze 
b) Haze Area c) Cloud on to Shadow d) Dehazed image 
e) ALOS AVNIR-2 after Cloud/Shadow, Haze Removed 
The result of removing cloud in Landsat ETM-- was also good, 
however, some of the pixels were found mis-replaced which 
might be because of the wider gap between acquisition date of 
Landsat 7 ETM- and ALOS PALSAR. 
4.2 Land Cover Classification and its Change Detection 
As presented in Table 1, overall accuracy is 80.9% and among 
the classes, Forest Land has less omission as well as 
commission errors. These errors for other LC classes, except 
Settlements, are relatively higher. This may be because of 
similar spectral reflectance for these LC classes that caused