Validating gap-filling of Landsat ETM+ satellite images in the Golestan Province, Iran

The Landsat series of satellites provides a valuable data source for land surface mapping and monitoring. Unfortunately, the scan line corrector (SLC) of the Landsat7 Enhanced Thematic Mapper plus (ETM+) sensor failed on May 13, 2003. This problem resulted in about 22 % of the pixels per scene not being scanned and has seriously limited the scientific applications of ETM+ data. A number of methods have been developed to fill the gaps in the incorrect images. Most of these methods have problems in heterogeneous landscapes. We applied and validated a simple and effective gap-fill algorithm developed by the US Geological Survey to a study area in the Golestan Province in the north of Iran. This algorithm operates under the assumption that the same-class neighboring pixels around the unscanned pixels have similar spectral characteristics, and that these neighboring and unscanned pixels share patterns of spectral differences between dates. For validation, unsupervised land use classification was performed on both gap-filled SLC-off data and the original “sound” data set. Classification results and accuracies were very comparable.