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Subpixel mapping is a promising way to increase the spatial resolution of classification results from images that have coarse spatial resolution but high temporal resolution. Existing subpixel mapping methods are not adequate for mapping linear features such as floodplain inundation. This study modified the commonly used pixel swapping (PS) algorithm and one of its derivatives, the linearised pixel swapping (LPS) algorithm, by employing finer resolution Digital Elevation Model (DEM) data. Results of a case study show that the modified method performs better than both the PS and LPS algorithms. It improves the accuracy and the Kappa coefficient by 4.78% and 0.11 in comparison with the PS algorithm. The spatial pattern of the inundation reveals fewer breakpoints and errors along the river channels. It is hoped that the proposed method will broaden the application of coarse resolution images in flood inundation detection. [ABSTRACT FROM PUBLISHER]