The Use of Unmanned Aerial Vehicles to Determine Differences in Vegetation Cover: A Tool for Monitoring Coastal Wetland Restoration Schemes

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.

[1]  G. Harvey,et al.  Modified sediments and subsurface hydrology in natural and recreated salt marshes and implications for delivery of ecosystem services , 2015 .

[2]  Chris J. Kennedy,et al.  The value of estuarine and coastal ecosystem services , 2011 .

[3]  Baofeng Su,et al.  Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications , 2017, J. Sensors.

[4]  Mark A. Fonstad,et al.  Topographic structure from motion: a new development in photogrammetric measurement , 2013 .

[5]  Daniel W. Llewellyn,et al.  The potential of small-Unmanned Aircraft Systems for the rapid detection of threatened unimproved grassland communities using an Enhanced Normalized Difference Vegetation Index , 2017, PloS one.

[6]  P. W. French.  Managed realignment The developing story of a comparatively new approach to soft engineering , 2006 .

[7]  J. Callaway.  The Challenge of Restoring Functioning Salt Marsh Ecosystems , 2005 .

[8]  Davey L. Jones,et al.  Grazing management in saltmarsh ecosystems drives invertebrate diversity, abundance and functional group structure , 2013 .

[9]  Charlotte E. L. Thompson,et al.  Parametrizing tidal creek morphology in mature saltmarshes using semi-automated extraction from lidar , 2018 .

[10]  Kalev Sepp,et al.  The use of medium point density LiDAR elevation data to determine plant community types in Baltic coastal wetlands , 2013 .

[11]  M. Westoby,et al.  ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications , 2012 .

[12]  J. S. Rodwell,et al.  British Plant Communities: Volume 5, Maritime Communities and Vegetation of Open Habitats , 2000 .

[13]  A. C. Armstrong,et al.  The Extent of Agricultural Field Drainage in England and Wales, 1971-80 , 1988 .

[14]  Katherine L. Brooks,et al.  Limited Vegetation Development on a Created Salt Marsh Associated with Over-Consolidated Sediments and Lack of Topographic Heterogeneity , 2014, Estuaries and Coasts.

[15]  Sedimentation rhythms and hydrodynamics in two engineered environments in an open coast managed realignment site , 2017 .

[16]  Daniel R. Parsons,et al.  Quantification of bedform dynamics and bedload sediment flux in sandy braided rivers from airborne and satellite imagery , 2019, Earth Surface Processes and Landforms.

[17]  H. M. Burgess,et al.  The evolution of embryonic creek systems in a recently inundated large open coast managed realignment site , 2018, Anthropocene Coasts.

[18]  K. Moffett,et al.  Remote Sens , 2015 .

[19]  G. Harvey,et al.  The impact of pre-restoration land-use and disturbance on sediment structure, hydrology and the sediment geochemical environment in restored saltmarshes. , 2017, The Science of the total environment.

[20]  John Robert Lawrence Allen,et al.  Morphodynamics of Holocene salt marshes: a review sketch from the Atlantic and Southern North Sea coasts of Europe , 2000 .

[21]  N. Burnside,et al.  Effective LiDAR-based modelling and visualisation of managed retreat scenarios for coastal planning: An example from the southern UK , 2015 .

[22]  S. Lane,et al.  Estimation of erosion and deposition volumes in a large, gravel‐bed, braided river using synoptic remote sensing , 2003 .

[23]  Andrea Rinaldo,et al.  Spontaneous tidal network formation within a constructed salt marsh: Observations and morphodynamic modelling , 2007 .

[24]  A. Gitelson,et al.  Novel algorithms for remote estimation of vegetation fraction , 2002 .

[25]  Lluís Brotons,et al.  Greenness Indices from a Low-Cost UAV Imagery as Tools for Monitoring Post-Fire Forest Recovery , 2019, Drones.

[26]  T. Bouma,et al.  Opposing Indirect Effects of Domestic Herbivores on Saltmarsh Erosion , 2018, Ecosystems.

[27]  H. M. Burgess,et al.  Sediment structure and physicochemical changes following tidal inundation at a large open coast managed realignment site. , 2019, The Science of the total environment.

[28]  Frédéric Pouget,et al.  Monitoring the Topography of a Dynamic Tidal Inlet Using UAV Imagery , 2016, Remote. Sens..

[29]  J. Bakker,et al.  Long-term changes of salt marsh communities by cattle grazing , 1990, Vegetatio.

[30]  Mark A. Friedl,et al.  Digital repeat photography for phenological research in forest ecosystems , 2012 .

[31]  P. Adam.  Saltmarshes in a time of change , 2002, Environmental Conservation.

[32]  K. Moffett,et al.  Alternative stable states of tidal marsh vegetation patterns and channel complexity , 2016 .

[33]  M. Hudson,et al.  Intertidal mudflat and saltmarsh conservation and sustainable use in the UK: a review. , 2013, Journal of environmental management.

[34]  Bijeesh KV,et al.  Opportunities for seagrass research derived from remote sensing: A review of current methods , 2020 .

[35]  K. Kiehl,et al.  Impact of different sheep grazing intensities on salt marsh vegetation in northern Germany , 1996 .

[36]  J. Dale.  The evolution of the sediment regime in a large open coast managed realignment site : a case study of the Medmerry Managed Realignment Site, UK , 2018 .

[37]  K. Sepp,et al.  Fine scale plant community assessment in coastal meadows using UAV based multispectral data , 2020, Ecological Indicators.

[38]  Conor J. Strong,et al.  The use of small-Unmanned Aerial Systems for high resolution analysis for intertidal wetland restoration schemes , 2020, Ecological Engineering.

[39]  P. Lawrence,et al.  Restored saltmarshes lack the topographic diversity found in natural habitat , 2018 .

[40]  E. Downing,et al.  CHANGES IN THE STRUCTURE OF MARSH SOILS FOLLOWING DRAINAGE AND ARABLE CULTIVATION , 1976 .

[41]  Takeshi Motohka,et al.  Applicability of Green-Red Vegetation Index for Remote Sensing of Vegetation Phenology , 2010, Remote. Sens..

[42]  Abolfazl Jaafari,et al.  Modeling multi-decadal mangrove leaf area index in response to drought along the semi-arid southern coasts of Iran. , 2019, The Science of the total environment.

[43]  N. Saintilan,et al.  Response of estuarine wetlands to reinstatement of tidal flows , 2010 .

[44]  Gemma L. Harvey,et al.  Understanding system disturbance and ecosystem services in restored saltmarshes: Integrating physical and biogeochemical processes , 2012 .

[45]  Xavier P. Burgos-Artizzu,et al.  utomatic segmentation of relevant textures in agricultural images , 2010 .

[46]  G. Meyer,et al.  Color indices for weed identification under various soil, residue, and lighting conditions , 1994 .

[47]  A. Grant,et al.  Does managed coastal realignment create saltmarshes with ‘equivalent biological characteristics’ to natural reference sites? , 2012 .