Rapid error assessment for quantitative estimations from Landsat 7 gap-filled images

The failure of the Scan Line Corrector (SLC) of the Landsat ETM+ (Enhanced Thematic Mapper Plus) instrument in 2003 had resulted in missing values for 22% of each scene. As the remaining pixels were of high quality, several procedures had been developed to fill the gaps and increase the usability of the SLC-off images. In this letter, a methodology is presented to assess the error when estimating quantitative parameters from gap-filled Landsat 7 images. The error from the gap-filling procedure was estimated using an external reference image. The methodology was applied in a Mediterranean river basin using two types of gap-filling methods and the error was estimated for leaf area index (LAI), actual evapotranspiration (ET_a) and soil moisture in the rootzone (SM_rz), three remotely sensed products which are commonly used in hydrological studies. The results suggest that the interpolation method had lower errors in all examined products. The proposed methodology is an imperative step that each user of gap-filled products could use to estimate the associated error before using the maps.