Vegetation presence Paulina(year 2 site), map based on L3A RapidEye data, image 05 June 2015,top of atmosphere radiance converted to surface reflectance and atmospheric correction using 6S, threshold NDVI=0.3. This is an unvalidated product for demo purposes only! For more information, please see EU FAST Internal Deliverable 3.8 (Example Geospatial products)

A Copernicus Sentinel-2 image was atmospherically corrected using Sen2Cor in SNAP 4, and then used to extract NDVI. Dike line was used to mask any area outside of the intertidal and subtidal zone. Coordinate system: WGS_84_UTM. Attribution: This product is developed by NIOZ for EU FAST project (Foreshore Assessment Using Space Technology). Contains modified Copernicus Sentinel data (2015/2016). See also https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice

Global vegetation change estimates are provided globally as GeoTIFF files with three bands and UINT16 pixel depth. Folder names indicate the region of the Earth to which the contents relate: Estimates are based on difference between vegetation presence/absence maps derived for the periods 16/071984-16/07/1989 and 01/01/2013-15/12/2016 using Google Earth Engine scripe Global_Veg_Change20.js Mean NDVI and seasonal NDVI fluctuation amplitude thresholds used for determination of presence/absence = 0.20. Bands: Band 1: Change estimate - 0= NoData, 1= Vegetation present in both times, 2= Vegetation loss, 3=Vegetation gain Band 2: Number of images used to estimate presence/abence of vegetation in 1984-1989 time period Band 3: Number of images used to estimate presence/absence of vegetation in 2013-2016 time period

Simulation is a non-hydrostatic XBeach-VEG simulation with and without vegetation. For more information about the possibilities of XBeach-VEG see https://publicwiki.deltares.nl/display/VegMod/XBeach-VEG

Estimates of changes in wave heights reaching the line of defence are provided as point features. Estimates are derived from manual digitisation of vegetated marsh margins in aerial photography for the years 1992 (t0) and 2013/14 (t1). The Digital Shoreline Analysis System (DSAS – Theiler et al. (2008)). DSAS computes shoreline change rates along approximately shore-normal transects. For this analysis a nominal 10m alongshore separation was used. Further details of accuracy will be available in forthcoming publications but the method is capable of resolving changes in the order of 0.1m/y. The marginal change estimates derived above were filtered to include only those points where a line to the nearest line of defence crossed only coherent marsh surface (i.e. no creeks or major pools/mudflats), such that changes in the width of the marsh could reasonably be expected to represent changes in hydrodynamic conditions at the sea wall. For each marginal change point, the nearest point on the UK Shoreline Management Plan vector was identified and the distance between the two measured. The marginal change rate measured using DSAS was then applied to estimate initial (t0) and end (t1) distances between the sea wall and the marsh margin. X-beach was run in 1D transect mode over idealised bathymetry and vegetation extents. Water levels, incident wave heights and cross-shore slopes were varied to represent the variety of such conditions expected across the domain. Vegetation representations in the model were taken from field data collected at Tillingham, UK, while the Cd term was calibrated against wave measurements made at Hellegat, NL. Model configuration was largely the same as that used for the EUFAST educational version except that the grid was refined to 5m cells to allow resolution of changes even within narrow fringing marshes. Parameter values (see X-Beach documentation for definitions) used are summarised in the table below: Parameter Value(s) Wavecon (wave heights Hm0) 1, 1.5, 2, 2.5, 3, 3.5, 4 WaveconS (steepness H/L) 7, 15, 30 waterLevelCon (above MSL) 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5 Coastalslopecon (1/n) 100, 150, 200, 250, 300, 400, 600, 800, 1000, 2000 Dir0 270 m 100 taper 0.01 wavint 30 gamma 0.5 nsec 1 ah 0.3 bv 0.00125 N 1125 Cd 0.19 Exhaustive combination of parameters resulted in 2310 model runs. From each run the significant wave height was extracted at distances along the vegetated transect (every 5 metres up to 100m, then at 250, 500, 1000 and 2000m). The effect of vegetation on significant wave height with distance (and its variance resulting from different topographic and hydrodynamics conditions) was then characterised by calculating the percentage of incoming wave height (Hm0) remaining at each distance interval. The mean and standard deviations for the percentage wave height remaining at each interval were then calculated. Two-term exponential functions were fitted to describe the variation with distance of the mean percentage wave height and the mean plus one standard deviation. The functions, where x is the distance along the vegetated transect, take the form: PercHsRemaining=a*exp(b*x) + c*exp(d*x) Coefficient values and goodness of fit are reported below. Function a b c d R-square Adj. R-square RMSE SSE Mean 28.6049 -0.0576 69.9979 -0.00183 0.9969 0.9965 1.259 33.31 Mean+1Sigma 9.8323 -0.1053 90.6793 -0.00093 0.9973 0.9969 1.046 22.96 The exponential functions derived above were then applied to estimate the change in the percentage of incoming wave height reaching the sea wall as a result of morphological changes over a 22 year period (1992-2014). No attempt is made to model the spatial distribution, or changes to, incoming wave conditions. The standard deviations represent a wider range of topographic and hydrodynamic conditions than most locations are likely to experience and therefore the uncertainty that they signify around the mean is conservative in the sense that it is likely to be an overestimate. Fields are: MarMovement – Change in margin position (m) along a line between the initial DSAS point estimate and the nearest point on the line of defence. MeanPercStart – Mean percentage of incoming wave height remaining at the line of defence at t0 MeanPercEnd – Mean percentage of incoming wave height remaining at the line of defence at t1 MeanPercDelta – Difference MeanPercEnd – MeanPercStart SDstart – Standard deviation of percentage wave height remaining at t0 SDend – Standard deviation of percentage wave height remaining at t1 SDofDiff – Standard deviation of MeanPercDelta

A Sentinel-2 image was atmospherically corrected using Sen2Cor in SNAP 4, and then used to extract Leaf Area Index (LAI), with the proviso that NDVI is larger than 0.3 to include marsh only. Dike line was used to mask any area outside of the intertidal and subtidal zone. Coordinate system: WGS_84_UTM. Attribution: This product is developed by NIOZ for EU FAST project (Foreshore Assessment Using Space Technology). Contains modified Copernicus Sentinel data (2015/2016). See also https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice

Earth's surface gained 115,000 km2 of water and 173,000 km2 of land over the past 30 years, including 20,135 km2 of water and 33,700 km2 of land in coastal areas. Here, we analyse the gains and losses through the Deltares Aqua Monitor — an open tool that detects land and water changes around the globe. Data published on http://aqua-monitor.appspot.com/

A Copernicus Sentinel-2 image was atmospherically corrected using Sen2Cor in SNAP 4, and then used to extract NDVI. Dike line was used to mask any area outside of the intertidal and subtidal zone. Coordinate system: WGS_84_UTM. Attribution: This product is developed by NIOZ for EU FAST project (Foreshore Assessment Using Space Technology). Contains modified Copernicus Sentinel data (2015/2016). See also https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice

A Copernicus Sentinel-2 image was atmospherically corrected using Sen2Cor in SNAP 4, and then used to extract NDVI. Dike line was used to mask any area outside of the intertidal and subtidal zone. Coordinate system: WGS_84_UTM. Attribution: This product is developed by NIOZ for EU FAST project (Foreshore Assessment Using Space Technology). Contains modified Copernicus Sentinel data (2015/2016). See also https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice

A Copernicus Sentinel-2 image was atmospherically corrected using Sen2Cor in SNAP 4, and then used to extract NDVI. Dike line was used to mask any area outside of the intertidal and subtidal zone. Coordinate system: WGS_84_UTM. Attribution: This product is developed by NIOZ for EU FAST project (Foreshore Assessment Using Space Technology). Contains modified Copernicus Sentinel data (2015/2016). See also https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice