Application of Remote Sensing Data in Large-Scale Monitoring of Wetlands

The present review examines existing technologies for mapping wetland ecosystems (WEs) based on remote sensing data. WEs are the most valuable ecosystems with a high conservation role. There are many classifications of WEs, including dozens of types. However, existing global or national-level WE maps typically do not consider their landscape specificity and are limited to only a few classes. Peatlands, swamp forests, high-productivity meadows, and riparian vegetation formations store substantial carbon reserves, which are released due to fires. The intensity of these fires has been increasing in recent years as a result of climate change. These issues necessitate the development of new large-scale monitoring methods for assessing the state of WEs, including mapping their types, determining biomass and carbon stocks, assessing the consequences of landscape fires, and evaluating greenhouse gas emissions and other combustion byproducts. First and foremost, it is necessary to develop a classification system for Russia’s WEs that considers their landscape diversity while being sufficiently generalized for satellite monitoring and annual updating of WE maps. Various remote sensing data types, including aerial imagery, lidar, and radar data, are used for WE mapping. The most promising direction for the development of WE monitoring technologies at the national level involves the use of long-term homogeneous time series data from MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite), in combination with ground-based calibration measurements and high-resolution satellite optical and radar data.