Super-resolution mapping of lakes from imagery with a coarse spatial and fine temporal resolution

The potential of super-resolution mapping (SRM) techniques for the representation of lakes was evaluated using both an established and a newly proposed method. Both super-resolution mapping techniques were typically able to provide representations that were visually and quantitatively more realistic than standard hard classifications. The new technique was able to represent more small lakes than the established technique. The results also demonstrate the value of using a time series of images as input to the super-resolution analysis, enabling researchers to usefully exploit the typically fine temporal resolution of coarse spatial resolution sensors for land cover mapping.

• A new super-resolution mapping used a combination of temporal image fusion, halftoning, 2d multiple notch filter and iterative morphological to represent lakes from coarse spatial resolution images.
• The shape characterization of the represented lakes was evaluated.
• The technique produced high accuracy and realistic characterizing of the shape of the lakes.