The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
1046 
In the formula, pi refers to RVI value of the pixel, n is the 
number of time serious. 
Histogram threshing method was used to threshold value set of 
standard deviation model according to historgram of stand 
deviation of time serious MODIS RVI data. First, analyzed 
shape of histogram, then determined possible cut-off point of 
farm field and non-farm field through special peaks of variance 
and mean value, finally, selection of cut-off point of farm field 
and non-farm field was determined by actual measurement by 
GPS and classification data by Landsat TM. 
The farm field information is extracted using above model and 
method, the result is as following (Figure 3(1) RVI-VAR). 
Compared with stand deviation of time serious MODIS NDVI 
data (Figure 3(2) NDVI-VAR), time serious first PCA (Princle 
Component Analysis) MODIS NDVI (Figure 3(2) RVI-VAR) 
and RVI (Figure 3(2) NDVI-VAR) data. 
RVI-VAR 
HDVI-VAR 
Figure 3(1) extraction of the farm field information through standard deviation model of time serious RVI and NDVI 
Figure 3 (2) extraction of the farm field information through time serious first PCA of RVI and NDVI 
Figure 3 various method for extraction of farm information 
Compared with extracting farm field information method of 
previous classification method and principle component 
analysis method using using time series MODIS data, the 
variance method is more efficient than others, and the accuracy 
exceed 80%, which verified by Landsat TM data. 
ACKNOWLEDGEMENTS 
This research was supported by The National Natural Science 
Fund (40771150); China's Western Development Program 
(KZCX2-XB2-03) ; Program for Changjiang Scholars and 
Innovative Research Team in University; Open foundation of 
Key Laboratory of Oasis Ecology (Xinjiang University) of 
Ministry of Education; Funded by Special Funds for Major 
State Basic Research Project (Grant No.2007CB714402) 
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