Coastal and estuarine wetlands provide a range of important ecosystem services, but are currently being damaged and degraded due to human activities, reduced sediment supply and sea level rise. Managed realignment (MR) is one approach used to compensate for the loss of intertidal habitat, however saltmarshes in MR sites have been recognised to have lower biodiversity than natural environments. This has been associated with differences in the physical functioning including the sediment structure, reduced hydraulic connectivity, and lower topographic variability such as the abundance of intertidal creek networks. Intertidal morphology, including creek networks, play an important role in supporting and regulating saltmarsh environments through the supply of sediment, nutrients and water, and in draining intertidal marshes. However, there is a lack of empirical data on the formation and evolution of topographic features and variability in saltmarsh environments. This is likely to be due to creek networks in natural marshes already being in a state of quasi-equilibrium, making MR sites an ideal environment to investigate creek development. However, traditional remote sensing techniques (such as LiDAR) tend to be relatively expensive, infrequent and at a coarse resolution meaning small, but important (cm-scale), changes are often missed. This study advances the ability to detect these small scale changes by demonstrating the suitability and potential applications of using the emerging photogrammetric method Structure-from-Motion (SfM) on images taken using a small-Unmanned Aerial System (sUAS). Three surveys from a rapidly changing, near-breach site were taken at the Medmerry Managed Realignment Site in July 2016, September 2017 and July 2018. A suitable degree of confidence was found between the modelled surface and independent check points (vertical root-mean-square-errors of 0.0245, 0.0704 and 0.1571 for 2016, 2017 and 2018 respectively). DSMs of Difference (DoD) analysis was performed to evaluate elevation change, with areas experiencing up to 85 cm of accretion between 2016 and 2018. However, when considering the error associated with both surveys, between 2016 and 2017, only 34.39 % of the survey area experienced change above the level of detection (LoD). In contrast, 76.97 % experienced change greater than the LoD between 2017 and 2018. Stream order analysis classified the creek networks into five orders in 2016 and four orders in 2017 and 2018, with 2016 having a higher abundance (291 in 2016 compared to 117 (2017) and 112 (2018)) and density (0.44 m/m 2 in 2016 compared to 0.27 m/m 2 in both 2017 and 2018) of creek networks. These results provide an innovative high resolution insight into the evolution of restored intertidal wetlands, and suggest that SfM analysis of images taken using a sUAS can be a useful tool with the potential to be incorporated into studies of MR and natural saltmarsh sites. sUAS analysis can, therefore, advance the management of these environments to ensure the provision of ecosystem se...

The loss of unimproved grassland has led to species decline in a wide range of taxonomic groups. Agricultural intensification has resulted in fragmented patches of remnant grassland habitat both across Europe and internationally. The monitoring of remnant patches of this habitat is critically important, however, traditional surveying of large, remote landscapes is a notoriously costly and difficult task. The emergence of small-Unmanned Aircraft Systems (sUAS) equipped with low-cost multi-spectral cameras offer an alternative to traditional grassland survey methods, and have the potential to progress and innovate the monitoring and future conservation of this habitat globally. The aim of this article is to investigate the potential of sUAS for rapid detection of threatened unimproved grassland and to test the use of an Enhanced Normalized Difference Vegetation Index (ENDVI). A sUAS aerial survey is undertaken at a site nationally recognised as an important location for fragmented unimproved mesotrophic grassland, within the south east of England, UK. A multispectral camera is used to capture imagery in the visible and near-infrared spectrums, and the ENDVI calculated and its discrimination performance compared to a range of more traditional vegetation indices. In order to validate the results of analysis, ground quadrat surveys were carried out to determine the grassland communities present. Quadrat surveys identified three community types within the site; unimproved grassland, improved grassland and rush pasture. All six vegetation indices tested were able to distinguish between the broad habitat types of grassland and rush pasture; whilst only three could differentiate vegetation at a community level. The Enhanced Normalized Difference Vegetation Index (ENDVI) was the most effective index when differentiating grasslands at the community level. The mechanisms behind the improved performance of the ENDVI are discussed and recommendations are made for areas of future research and study.

Managed realignment (MR) sites are being implemented to compensate for the loss of natural saltmarsh habitat due to sea level rise and anthropogenic pressures. However, MR sites have been recognised to have lower morphological variability and coverage of saltmarsh vegetation than natural saltmarsh sites, which have been linked with the legacy of the historic (terrestrial) land use. This study assesses the relationship between the morphology and vegetation coverage in three separate zones, associated with the legacy of historic reclamation, of a non-engineered MR site. The site was selected due to the phased historical reclamation, and because no pre-breaching landscaping or engineering works were carried out prior to the more recent and contemporary breaching of the site. Four vegetation indices (Excess Green Index, Green Chromatic Coordinate, Green-Red Vegetation Index, and Visible Atmospherically Resistant Index) were calculated from unmanned aerial vehicle imagery; elevation, slope, and curvature surface models were calculated from a digital surface model (DSM) generated from the same imagery captured at the MR site. The imagery and DSM summarised the three zones present within the MR site and the adjacent external natural marsh, and were used to examine the site for areas of differing vegetation cover. Results indicated statistically significant differences between the vegetation indices across the three zones. Statistically significant differences in the vegetation indices were also found between the three zones and the external natural saltmarsh. However, it was only in the zone nearest the breach, and for three of the four indices, that a moderate to strong correlation was found between elevation and the vegetation indices (r = 0.53 to 0.70). This zone was also the lowest in elevation and exhibited the lowest average value for all indices. No relationship was found between the vegetation indices and either the slope or curvature in any of the zones. The approach outlined in this paper provides coastal managers with a relatively low-cost, low-field time method of assessing the areas of vegetation development in MR sites. Moreover, the findings indicate the potential importance of considering the historic morphological and sedimentological changes in the MR sites. By combining data on the areas of saltmarsh colonisation with a consideration of the site’s morphological and reclamation history, the areas likely to support saltmarsh vegetation can be remotely identified in the design of larger engineered MR sites maximising the compensation for the loss of saltmarsh habitat elsewhere.

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