MODIS method is a sensor to get the data by multi detector observation

among that 1km resolution waveband needs 10 detectors to scan at the same time

500m resolution waveband needs 20 detectors

and 250m resolution waveband needs 40 detectors. The adoption of this technology has improved the scanning and data collection efficiency. However

there is a problem of the consistency between so many detectors

especially after the satellite is launched into the space the unexpected electromagnetism environment

it is very difficult to make so many detectors completely consistent. Therefore

the response discrepancy between the detectors will cause certain stripe in MODIS sensor

and the most serious stripe is in MODIS waveband 33-36. Some detectors of waveband 36 and 35 cannot reach the original defined NE Δ T . More stripe appears in the 6th

7th and 8th detectors of waveband 34

and the 1st detector of waveband 33. Stripe also exists in other infrared waveband and visible waveband; there the stripe of window waveband is usually lower

while the stripe of atmospheric detecting waveband is more serious. This kind of stripe will cause much serious influence to the retrieving precision of MODIS quantitative products. In order to reduce the influence of MODIS stripe and improve the retrieving precision of remote sensing quantified products as soon as possible

we developed a wavelet analysis method to de stripe MODIS data. With this method

we remove the stripe of some different wave bands. These are waveband 36

35

34 and 33 detecting the phsical character of the cloud top

waveband 30 detecting the ozone

waveband 29

28 and 27 detecting the water vapor

and the waveband 25

24 and 23 detecting the atmospheric temperature. We describe a wavelet method for recovery of MODIS data from its stripe signals. Our work is organized into four broad sections. Section 1 will introduce wavelet shrinkage method for de noising noisy data; compare the character of the wavelet method and the FFT method in de noising processing. The objective of section 2 to find out the scale of MODIS stripe by the wavelet analysis for MODIS stripe data using continues wavelet transforms. Section 3 analyses stripe noise data pattern for the MODIS level 1B stripe data

present the wavelet shrinkage method for MODIS level 1B data. Section 4 will provide a comparson for MODIS cloud product and atmospheric profile product between the original data and de striped data. We can find that there is an improvement in MODIS cloud product and atmopheric profile product after de striping. And we can get more understanding for the stripe regular pattern.