Evaluation of SAR C-band interferometric coherence time-series for coastal wetland hydropattern mapping

摘要

South America is the continent of wetlands, which represents more than 20% of its surface. Since the ecological integrity of wetlands strongly depends on their water sources and dynamics, it is fundamental to understand their hydrology. Large wetlands are usually located in inaccessible areas where remote sensing results are a fundamental tool for wetland monitoring, providing information over a broad range of spatial and temporal scales. Radar spaceborne sensors provide an excellent all-weather tool for monitoring and recent investigations have also shown that Interferometric SAR (InSAR) can be very valuable for wetland monitoring in addition to its regular uses in DEM generation and surface deformation analyses. The availability of new SAR satellites such as the Sentinel 1 and SAOCOM missions, with short revisit times and open data policies, repeat-pass interferometry can now provide long time-series of coherence for wetland monitoring. In this article, we used a SOM neural network to cluster a yearly series of Sentinel 1 B coherence images from the coastal plain of Samboromb'on Bay, Argentina, into temporal coherence patterns. The timing and coherence values of these patterns were interpreted in terms of landcover, vegetation phenology, water sources, and waterlogged condition. Although the SOM patterns did not show a one to one relationship with landcover types nor with the main water sources, their spatial distribution and temporal signature of coherence gave information on wetlands with different water dynamics. A key outcome of our study was that temporal patterns of coherence could be used to assess the impacts of land-use practices on wetland functioning, which deserves further exploration. The spatial distribution of the temporal coherence patterns can be used as a hypothesis for wetland hydropatterns, a key to hydrological functional type wetland classification. This approach can help us gain a better understanding of complex wetlands and foster their sustainable management, particularly combined with in situ fieldwork and other remote sensing sources, particularly repeat pass L-band coherence, which can give a better indication of soil wetness.