Wetland ecosystems provide essential services for the subsistence of life on Earth; however, these ecosystems face constant external threats that affect and change their natural processes and dynamics.
Significant knowledge gaps exist on multiple aspects, components, and interactions of wetlands worldwide. Multitemporal Earth observations offer an excellent opportunity to address these knowledge gaps and are sometimes the only source of information in remote and non-instrumented areas.
This session focuses on studies using Earth observation data (from passive and active sensors) to explore and understand wetland dynamics, processes, and services, as well as their broader connections with other elements of the landscape. It encompasses investigations into various components and processes of wetland ecosystems, such as (but not limited to) water dynamics, vegetation changes, disturbances, soil moisture, biodiversity, across a range of wetland types (e.g., marshes, swamps, fens, bogs, peatlands, lakes, ponds, coastal wetlands).
The session also encourages studies utilizing multi-sensor approaches, as well as machine learning, deep learning, and artificial intelligence technologies, to develop innovative solutions for wetland monitoring, conservation, and restoration.