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Explanation of the problem:

On 31 May 2003 the Landsat 7 Enhanced Thematic Mapper (ETM+) sensor had a failure of the Scan Line Corrector (SLC). Since that time all Landsat ETM+ images have had wedge-shaped gaps on both sides of each scene, resulting in approximately 22% data loss. These images are available for free download from the USGS GloVis website and are found in the L7 SLC-off collection.

source: Yale University

Can I use Qgis instead of proprietary software (ENVI, Erdas....) to fill the gaps?

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  • To what quality do you need to fill the gaps? Are they near edge? Will images of other dates be of use? The starting point would be (I think) to use the mask layers which are supplied with the USGS Landsat 7 ETM data sets.
    – Willy
    Commented Jul 27, 2012 at 10:45

2 Answers 2

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You could try the gdal_fillnodata tool which is also available in QGIS via the Raster->Analysis->Fill nodata menu. It uses an inverse distance weighting (IDW) interpolation. I just tried both that method and the single date Triangulation interpolation (in ENVI) and gdal_fillnodata looked much better. If you want to merge multiple dates, you might have to implement the localised linear histogram matching methodology in python (GDAL+Numpy) to get it to look good.

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One of the co-authors of this paper provides an open source implementation in IDL for their algorithm to fill gaps in SLC off data, dubbed NSPI algorithm (Neighborhood Similar Pixel Interpolator).

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