The Study On MODIS Image Data Preprocess Technique

MODIS (Moderate Resolution Imaging Spectroradiometer) is an important data getting instrument of information onboard the Terra and Aqua satellites. These data as the substitute of NOAA-AVHRR data are familiar with people. The data have been mainly used in dynamic monitoring of natural disaster, changes in landscape and vegetation, global net primary productivity, ecological environment, climate changes, and ocean.Data preprocess is a key step before the data have been used. It will affect the utilization further. The objective of this study is to develop approaches to correct the stripe noises and overlaps at the edge of MODIS imagery. The suitable geometric correction methods for MODIS data are studied as well. The templet interpolation algorithm is used to remove stripe noises. The results show that this method is valid, and is effective to preserve the spectral characteristic of non-noise pixel. We use the correlation of data between the neighbor scan lines to get the overlay pixel number, and then remove the overlay data. The bilinear interpolation method is applied to assign the pixels with the overlap data. The result shows that the data overlay phenomenon is removed, image quality is improved, and pixel value has been enhanced. In this study, two geometric correction methods are introduced. Based on the characteristics of MODIS data, geo-location of the experimental area, and the error distribution patterns of different projections, we conclude that the Albers Conical Equal Area projection is feasible for the geometric correction.