Sub-pixel analysis in shoreline mapping

Malaysia’s shoreline is dynamic and constantly changing. Although the shoreline may be mapped accurately from fine spatial resolution imagery, this is an impractical approach for use over large areas. An alternative approach using coarse spatial resolution satellite sensor imagery, addressed here, is to fit a shoreline boundary at sub-pixel scale. This paper investigates the effects of utilizing relatively coarse spatial resolution satellite sensor imagery to produce accurate shoreline maps. For the purposes of this research a 1m spatial resolution IKONOS satellite sensor image was used to define the actual location of the shoreline. This image was degraded to spatial resolutions of 16 m and 32 m, comparable to that of widely used civilian remote sensors. The coarse spatial resolution images derived were used in the evaluation of four methods for shoreline mapping. The conventional method based on hard classification provided an inaccurate and inappropriate representation of the shoreline. Super-resolution methods based on sub-pixel information derived from a soft classification provided accurate and realistic prediction of the shoreline. The most accurate prediction of the shoreline, with RMSE less than 2.1 m and 5.2 m for all the shorelines at 16 m and 32 m spatial resolutions respectively, were derived from a method based on simulated annealing.