Wavelet Transform In The Modis Lai Noise Reduction

MODIS remote sensing data is a new generation source of satellite remote sensing. It has the extensively applied foreground in many researches such as ecology study,the environment monitor, global weather variety and the agriculture resources inquisition etc. MODIS LAI (Leaf Area Index) is one of the main types of the MODIS data product. It is an very important parameter of vegetable biophysics ,and controls many biology and physics processes of vegetable, such as photosynthesis, breathe, steams evaporability, carbon cycle processes etc. However, the quantity of the MODIS data product is not good enough because of noise.Wavelet analysis is a valid analyzing means.Recently,with the improvement of wavelet theory,wavelet analysis has penetrated into many fields. Image denoising via wavelet transform is one success of wavelet applications.In this paper, a algorithm based on wavelet for time-series LAI's image de-nosing are introduced.First, combining with the quantity control information (QC)of the MODIS data product, uses CUBE law increase succession MODIS LAI the usefulinformation, then the introduction wavelet transformation to remove succession MODIS the LAI data product noise. Finally, this paper proposes some appraisals pattern to MODIS LAI data product after this algorithm model processing. The experiment indicates, the algorithm we proposed to remove succession MODIS LAI data product has the certain validity.