Title :
A Simple Data Assimilation Method for Improving Estimation of MODIS LAI Time-series Data Products Based on the 2-Dimensional LMS Adaptive Filter
Author :
He, Binbin ; Tong, Ling ; Xu, Wenbo ; Han, Xili ; Yuan, Hui ; Zhou, Maohui ; Li, Xiaoli ; Li, Xiaowen ; Wang, Jindi
Author_Institution :
Inst. of Geo-Spatial Inf. Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu
fDate :
July 31 2006-Aug. 4 2006
Abstract :
Leaf area index (LAI) is an important parameter for describing vegetation canopy structure in the terrestrial ecosystem on the global, continental and regional scales. In this paper, a simple data assimilation method for improving estimation of MODIS LAI time-series data products based on a new 2-D LMS (two-dimensional least mean square) adaptive filter was proposed. Firstly, The new 2-D LMS adaptive filter algorithm is introduced and analyzed. Secondly, A simple data assimilation method for improving estimation of MODIS LAI time-series data products based on the new 2-D LMS adaptive filter and quality control data of MODIS LAI is proposed. Finally, the experiments are performed based on the simple data assimilation method using MODIS LAI data products from 2000 to 2005 of southwestern China.
Keywords :
adaptive filters; data assimilation; geophysical techniques; vegetation; 2D LMS adaptive filter algorithm; 2D least mean square adaptive filter algorithm; AD 2000 to 2005; MODIS LAI time-series data products; data assimilation method; leaf area index; southwestern China; terrestrial ecosystem; vegetation canopy structure; Adaptive filters; Data assimilation; Ecosystems; Least squares approximation; MODIS; Quality control; Signal processing; Two dimensional displays; Vegetation; Working environment noise;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on
Conference_Location :
Denver, CO
Print_ISBN :
0-7803-9510-7
DOI :
10.1109/IGARSS.2006.440
