Full text: Proceedings; XXI International Congress for Photogrammetry and Remote Sensing (Part B1-3)

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
954 
And we show four scenes of generated LAI map in fig 
8,,which are 57,145,177 and 209 day of yeae, respectively. 
X w( T¡ > r i ~ x b ( r ¡ ))] ( 2 ) 
= + — ; 
Yj w ( r .' r j) 
y=i 
3. CONCLUSION AND DISCUSSION 
Because of the low spatial resolution, although MODIS LAI 
can give us time serial data, can’t meet our study need. In this 
paper, based on the BJ-1 LAI estimation, fusing on time series 
MODIS LAI products, and the BJ-1 LAI is used to adjust this 
curve of time-series LAI, we generate the high spatial and 
temporal resolution LAI product of Beijing-1 images. And this 
method is very useful for us to get high spatial and temporal 
resolution LAI product by fusing the data with low spatial 
resolution, but high temporal resolution and the data high 
spatial resolution, but low temporal resolution, and taking its 
advantages, respectively. So we can get the right data for our 
study. Through this study, we can get the LAI products of 
Beijing-1 images, which is with the high spatial resolution and 
high time resolution (32m, 4-day product). This product will 
provide more information of vegetation for BJ-1 microsatellite 
data applications. But this method has still in the course of 
testing, and next we would apply it to the larger area. 
177 day 209day 
Fig. 8 The generation of time serial Beijing-1 LAI images. 
57 day 
145day 
ACKNOWLEDGEMENTS 
We thanks for BLMIT supporting us free Beijing-1 images. 
This research was supported in part by the National Natural 
Science Foundation of China(No.40701116,40571107), the 
open fund about Beijing-1 image., and the Special Funds for 
Major State Basic Research Project (2007CB714407), National 
863 Program (2002AA130010) 
REFERENCE 
[1] Bonan, G. B. (1993). Importance of leaf area index and 
forest type when estimating photosynthesis in boreal forests. 
Remote Sensing of Environment 43: 303-314. 
[2] Chen Zhengchao, L. W., ZHANG Hao,L IU Xiang,ZHANG 
Liang (2006). The Geometric Evaluation of Be ijing-1 
Microsatellite Multispectral Images. Journal of Remote 
Sensing 10(5): 690-696. 
[3] G D. Badhwar, R. B. M., N. C. Mehta (1986). 
Satellite-derived LAI and vegetation maps as input to 
global cycle models—A hierarchical approach. Int. J. 
Remote Sens 7: 265-281. 
[4] Jing M. Chen, J. C. (1996). Retrieving leaf area index of 
boreal conifer forests using Landsat TM images. 50(2): 
153-162. 
[5] Marie Weiss, F. B., Sébastien Garrigues and Roselyne 
Lacaze (2007). LAI and fAPAR CYCLOPES global 
products derived from VEGETATION. Part 2: validation 
and comparison with MODIS collection 4 products. Remote 
Sensing of Environment 110: 317-331. 
[6] Mehul R. Pandya, R. P. S., Karshan N. Chaudhari, Govind 
D. Bairagi, Rajesh Sharma,Vinay K. Dadhwal, and Jai 
Singh Parihar (2006). Leaf Area Index Retrieval Using 1RS 
LISS-III Sensor Data and Validation of the MODIS LAI 
Product Over Central India. IEEE TRANSACTIONS ON 
GEOSCIENCE AND REMOTE SENSING 44(7): 
1858-1865. 
[7] Nikolay V. Shabanov, D. H., Wenze Yang, Bin Tan. (2005). 
Analysis and Optimization of the MODIS Leaf Area Index 
Algorithm Retrievals Over Broadleaf Forests. IEEE 
TRANSACTION ON GEOSCIENCE AND REMOTE 
SENSING 43(8): 1855-1865.
	        
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