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The number of salt marsh restoration schemes is set to increase substantially this decade, driven by three key factors: a) legislative requirements to compensate for losses; b) a transition to a natural approach for coastal management; and c) growing interest in ecosystem services salt marshes provide. Monitoring is key to evaluating the success of restoration projects and can inform future projects. However, many schemes have been found to use ineffective monitoring strategies. A major barrier to developing effective monitoring programmes has been the resources required to carry out frequent, spatially explicit surveys using traditional survey methods, which will become an even greater problem as more schemes are created. Consequently, improvements to survey methods are required. This project aims to improve our understanding of the role that remote sensing combined with field data can play in assessing the development of salt marsh restoration programmes. To address this aim, monitoring has been carried out at a new restoration site in the Adur estuary, on the south coast of the UK, since its creation in 2019. Field data has been collected, including biannual changes in species cover along transects. These surveys have found positive development at the Adur site, with clear successional changes in vegetation cover. Drone flights have also been carried out at the site to accompany the transect surveys, with machine learning algorithms used to develop models of the observed changes. Preliminary testing has found the machine learning models produce accurate results, demonstrating that remote sensing can be a valuable asset to existing monitoring practices.
Agate et al. (Fri,) studied this question.