American Journal of Applied Sciences

Using IRS Products to Recover 7ETM+ Defective Images

Mobasheri Mohammad Reza and Sadeghi Naeini Ali

DOI : 10.3844/ajassp.2008.618.625

American Journal of Applied Sciences

Volume 5, Issue 6

Pages 618-625

Abstract

On May 31st, 2003, Landsat 7 faced an anomaly in the Scan Line Corrector (SLC) normal operation. This malfunctioning of SLC caused the individual scan lines alternately overlap each other and consequently produce large gaps at the edges of the image. Regarding the unique specification of ETM+ sensor on board of Landsat-7 satellite such as its spectral bands in the shortwave IR and TIR region and its suitable spatial resolution which is ideal for most of the scientific researches, a technique for the reconstruction of the defected images due to the SLC malfunctioning, was built up. Due to the availability of IRS/1D LISS-III images for our region of interest i.e., southwest of Iran, it was decided to use these images to recover 7ETM+ products. The procedure in reconstructing the defected 7ETM+ images is divided in to two stages. In the first stage, after implementation of some preprocessing to both LISS-III and 7ETM+, a linear regression model between bands 3 and 4 of 7ETM+ and bands 2 and 3 of LISS-III was setup. This model is used to fill up the missing places in 7ETM+ defected image and produced two new images in bands 3 and 4. In the second stage, these two newly reconstructed images of 7ETM+ were used to recover images of 7ETM+ in other spectral bands. At this stage, two methods were introduced, one using linear relationship between band 3 and bands 1 and 2 and in the second method we introduced a planar relationship between bands 3 and 4 with each one of bands 5, 6 and 7. The models are applied to few images and are found to be fairly reliable. The primary and necessary conditions for applying these methods have been explained in detail.

Copyright

© 2008 Mobasheri Mohammad Reza and Sadeghi Naeini Ali. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.