Since the 1990s, many peatlands that were drained for peat extraction and agriculture in Russia have been abandoned with high CO₂ emissions and frequent fires, such as the enormous fires around Moscow in 2010. The fire hazard in these peatlands can be reduced through peatland rewetting and wetland restoration, so monitoring peatland status is essential. However, large expanses, poor accessibility, and fast plant succession pose as challenges for monitoring these areas without satellite images. In this study, a technique involving multispectral satellite data was used to identify six land cover classes that meet the requirements for peatland monitoring using the Meschera National Park as the testing area. This park is the largest area of once-exploited and now rewetted peatlands. However, data from one scanner are often insufficient to successfully implement this technique. In this study, we compared the land cover classifications obtained by using data from Spot-5, Spot-6, Landsat-7, Landsat-8, and Sentinel-2 satellites. The Spot-6 data were insufficient, despite having a higher spatial resolution, due to the lack of a shortwave infrared (SWIR) band. The high classification accuracy attained using data from other sensors enabled their combined use to provide an acceptable accuracy in the final product. The classification results were compared using minimum distance Erdas Imagine and the object-oriented ScanEx Image Processor, and the classification accuracy was similar between satellite images, which facilitates the transition from one method to another without quality loss. The proposed and tested approach can be used to analyze the status of abandoned and rewetted peatlands in other locations for the inventory and prioritization of sites for rewetting and restoration, monitoring status changes, and assessing restoration efficacy. The comparability of the data from different sensors allows for the combination of classified images and creates new possibilities for time series analysis.

On examples of n × 100 m² permanent plots laid in 2005 on peatlands disturbed by quarrying and milling peat extraction in Meshchera National Park (central European Russia), changes in vegetation cover and environmental factors during self-revegetation, the impact of wildfire, and rewetting are considered. Peat extraction pits are overgrown with floating mats, on which mire, predominantly mesotrophic, vegetation is formed. Cofferdams with retained original mire vegetation contribute to the formation of a spatially diverse mire landscape, but they can also be prone to natural fires. The environmental conditions at the abandoned milled peat extraction sites do not favour natural overgrowth. The driest areas can remain with bare peat perennially. Such peatlands are the most frequent targets of wildfires, which have a severely negative impact and interrupt revegetation processes. Alien plant species emerge and disappear over time. To prevent wildfires and create conditions favourable for the restoration of mire vegetation, rewetting is required. With an average ground water level (GWL) during the growing season of −5 to +15 cm, mire vegetation can actively re-establish. Communities with near-aquatic and aquatic plants can form on flooded areas with GWL of +30. This generally contributes to both fire prevention and wetland diversity.