A multi‐scale segmentation approach to filling gaps in Landsat ETM+ SLC‐off images

Abstract

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge‐shaped scan‐to‐scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi‐scale segment model, derived from a previous Landsat SLC‐on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC‐off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap‐fill algorithm used in deriving the segment‐based gap‐fill product, and presents the results of the gap‐fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional‐scale studies, general land cover mapping (e.g. forest, urban, and grass), crop‐specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per‐pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

Acknowledgments

Many thanks to Mike Craig (US Department of Agriculture, National Agricultural Statistics Service) and Richard Allen and Masahiro Tasumi (University of Idaho) for their testing and valuable feedback on the prototype products. Thanks also to Ron Hayes and Rachel Kurtz (USGS/EROS) for their valuable comments on this manuscript. Work was performed under US Geological Survey contract no. 03CRCN0001.

Notes

1. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the US Government.