A modular, user-centered digital platform for monitoring peatland ecosystem services

Abstract Peatlands are important ecosystems providing a critical range of ecosystem services such as carbon storage, habitat for biodiversity and water regulation. Most peatlands in Germany are drained, causing carbon emissions, land subsidence and ecosystem service loss. Rewetting and sustainable peatland management practices, such as paludiculture, are gaining interest as they allow the productive use of wet or rewetted peatlands while providing ecosystem services and supporting biomass production. Comprehensive monitoring of peatlands is essential for the implementation of rewetting and peatland management but also forms the basis for creating financial incentives, such as for emission certificates or improved sales opportunities for the biomass. However, current monitoring techniques are unable to ensure scalable and efficient ecosystem monitoring in terms of cost, reliability, resolution and integrity. Here, we report on a project that addresses the development of a modular, user-centered digital platform for monitoring peatland ecosystem services. We present the research, establishment and deployment of an integrated, multi-purpose sensor network as a large-scale monitoring approach. The platform utilizes sensor networks and remote sensing (RS) through unmanned aerial vehicles (UAV), artificial intelligence (AI) and visual computing (VC). Key components include the automated recording and processing of water level maps via real-time sensor networks and the classification of vegetation using UAV imagery and AI. These data streams are integrated into transferable models for assessing ecosystem services to verify carbon and/or biodiversity credits and support paludiculture at regional and international scales.