Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery

Abstract

Ponds and tidal courses are significant landforms that frequently arise in marshes and tidal flats environments. An understanding of their development and permanence is relevant to determine future dynamic processes that alter tidal flats and salt marshes environments, such as changes in the sea level, increase in the wave activity, and some other variations associated to the climate change. Direct access for monitoring in these regions is complex, extremely expensive and not always feasible. Remote sensing imagery represents a monitoring alternative, but requires the research of specific image processing procedures to extract the information concerning to these environmental studies. In this work, we developed a methodology for assessing the relevant morphological parameters of ponds and tidal courses using Google Earth imagery. An automatic classifier identifies these landforms as such (accuracy over 86%), producing a shape descriptors dataset. Then, ponds and tidal courses in tidal flats are morphologically characterized, and their behavior is compared to the surrounding environment. Subsequent analysis found significant differences in morphological characteristics that arise independently of the marsh environmental conditions. The evidence suggests that the evolution processes of the depressions in salt flat environments are clearly different in comparison with salt marshes environments. In salt marshes, the permanence and evolution of the depressions is related to the age of marshes, whereas in tidal flats the dynamic processes and sediment input have influence on depressions evolution.