product that will be 
ystem(EOS) standard 
scenes where land, 
e retrieved based on 
€ to clouds and thick 
es of sequential tests 
bservations. 
eld 
   
Aerosol 
ierosol 
oh 
" Cloud top 
field of the MODIS 
fference cloud index 
inces observed in 
flectances. 
d as the difference of 
61m) and a near 
ed as the difference 
66um), and it is very 
land and cloud at 
um) the Spectral 
> vapors from the 
sy. So the NDCI is 
6 
6 (1) 
oud; when the NDCI 
NDCI is negative the 
w is less than the 
ed as bare soil when 
NDCI is between 0 
0.5; NDCI value of 
t a suitable 
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tection. The results 
cloud removals are 
> replace by its ‘real 
; or other land cover 
ming from the same 
   
  
      
      
Generally speaking, there are 3days, 8 days, 10days, 15days, 
and one month, three months’ time interval for the series of 
composition. Variable time interval means different 
composition effects. Long is the time interval well is cloud 
removal. But every coin has two sides. During the long time 
interval the real pixel maybe change especially in the snowy 
weather. It is wise to set an appropriate time interval. With the 
the time series images the cloud pixel would be replaced by the 
clear pixel. E.g. 
BE or fiy) 
C y) 20 
C, y) 20 
fef 
eot (2) 
6 yel 
f£ fy) 
Cy) 21 
C (s y) 0 
where /u/C53» 5,05») are reflectivity from MODIS 
band; 
x, yis the row and column of the pixel; 
C053. 059) are cloud mask from different images. 
When its value equals 1 it means cloud; when its value 
equals 0 it means no cloud. 
3. STUDY AREA AND DATA 
3.1 Study area 
Our study area is located in the southwest of Tibetan Plateau. 
The geographic location of this area ranges in longitude from 
80?0'45.63"E to 85 ?0'8.01"E and latitude from 30 °48.9”N to 
32?4.54"N. 
Tibet is contiguous to Xinjiang Uygur autonomous Region and 
Qinghai Province by the Kunlun and the Tanggula Mountains 
on the north, looks at Sichuan Province across the Jinsha River 
on the east, is connected with Yunnan Province on the southeast, 
borders Burmese, India, Bhutan, Sikkim, Nepal and Kashmir. 
It has a distance of 2400 km. in length, 200-300 km in width. Its 
average altitude is over 6000 m, the highest range in the world-- 
-Mt. Qomolangma, stands in the middle of the Himalaya range. 
In its surrounding area of more than 5000sq km, there are four 
of the world's 8000-meter peaks and thirty-eight of the 7000- 
meter peaks. 
Figure 2 shows the location of study area in the SRTM DEM 
map. The resolution of SRTM DEM data is about 90m. All the 
data cover the whole Plateau is 32 longitudes and 15 latitudes. 
The range of coordinate is from E73 to E104; and from N26 to 
N40. The total data is 480 scenes. In order to compare with 
MODIS data conveniently, SRTM DEM data is reprojected to 
500m and mosaic together. 
  
  
   
   
  
   
   
  
  
  
   
   
  
   
  
  
    
     
    
   
    
   
  
  
    
   
  
    
   
   
    
   
   
   
  
  
    
    
   
  
   
   
   
    
    
   
    
  
   
  
   
  
   
  
  
  
  
  
  
  
  
  
  
Figure2. The topographic map of the Tibetan Plateau from 
SRTM DEM data (Lina X. 2009) 
3.2 Data 
MODIS is an imaging spectroradiometer that includes a set of 
individual detector elements to provide imagery of the Earth’s 
surface and clouds in 36 discrete, narrow spectral bands from 
approximately 0.4 to 14.0pm. Its main land surface objectives 
are to study global vegetation and land cover, global land- 
surface change, vegetation properties, surface albedo, surface 
temperature, and snow and ice cover on a daily or near daily 
basis. MODIS can provide much higher spatial resolution than 
the NOAA AVHRR instruments. The spatial resolution varies 
with spectral band and ranges from 250 m to 1 km at nadir. 
The data used in this study are MODIS surface reflectivity data 
productions that include 7 bands with 500m resolution. For the 
research nearly a series of scenes were downloaded at least one 
month at the same area. 
4. CLOUD DETECTION DREE 
4.1 Cloud and snow detection 
Many cloud decision methods are built on decision trees. The 
decision trees were designed based on empirical studies and 
simulations. 
Here, we built a decision tree based on NDCI and image 
composition. NDCI is defined as the difference between 0.66um 
and 1.64um. Here for the MODIS data, visible band means the 
MODIS band 1 (0.66um) and the short wave infrared band 
means the MODIS band 6 (1.640um). 
Bandl = band6 (2) 
Bandl 4 band6 
NDCI - 
Firstly; computing NDCI values based on equal (2). With the 
threshold snow pixel without cloud would be confirmed based 
on the fact that the repectivity of snow is less than the cloud. 
Secondly, bare soil and vegetation would be set when the NDCI