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 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

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

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

Coastal digital terrain model's (DTMs) are a critial component of MiSAFE. They are the geospatial data over which all wave propagation calculations are made and may form an important component of classification schemes; by defining elevation ranges over which different types of intertidal vegetation occur. EU/ESA's Copernicus, high resolution Sentinels (S1 and S2) and the NASA/USGS Landsat missions can potentially help create inter-tidal elevation maps. Elevation maps were developed using the Google Earth Maps. If you have any questions concerning the data, please contact Edward Morris.

Estimates of the change in coherence of marsh surfaces are provided as a polygon vector layer on a 30m grid. Coherence is defined as the percentage of a 30m cell that is covered by vegetation. The product therefore describes the change in this value over time. The product is based on a modified trend analysis of NDVI values derived from the LandSat archive. The time period of observations varies on a per-pixel basis depending on cloud presence and overpass schedules, but is approximately mid-1980s to 2016. The satellite-derived trends are calibrated against changes observed in aerial photography from 1992 (panchromatic, 25cm pixels) and 2014 (RGBI, 20cm pixels), and validated using the same photography at different locations (R-square = 0.81). Changes in percentage vegetation cover are then discretised into 8 classes and provided as a text field (‘PVC_Text’). String representations of change range from ‘Less than -25%’ (meaning that the percentage of the cell that is covered by vegetation has decreased by 25% or more over the observation period) to ‘More than +50%’ (meaning that the percentage of the cell that is vegetated has increased by more than 50% over the observation period). An additional field is provided entitled ‘SMExts_Class’. This field represents the proportion of the 30m grid cell that was covered by vegetation (ca. 2006-2009) according to the saltmarsh extents layer of Phelan et al. (2011). The data are provided in ten classes as numeric values signifying the upper bound of deciles. Further details of the method and non-discretised data will be provided in forthcoming publications. Phelan, N., Shaw, A., and Baylis, A. (2011). The extent of saltmarsh in England and Wales:2006 – 2009.

Coastal digital terrain model's (DTMs) are a critial component of MiSAFE. They are the geospatial data over which all wave propagation calculations are made and may form an important component of classification schemes; by defining elevation ranges over which different types of intertidal vegetation occur. EU/ESA's Copernicus, high resolution Sentinels (S1 and S2) and the NASA/USGS Landsat missions can potentially help create inter-tidal elevation maps. Elevation maps were developed using the Google Earth Maps. If you have any questions concerning the data, please contact Edward Morris.

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

The newly developed Coastal Hazard Wheel (CHW) of UNEP has been applied for the entire South American coastline. The CHW enables coastal zone managers to clearly understand the governing processes and expected threats for a given coastal stretch. A validation dataset is required to test the applicability and accuracy of the CHW for assessing coastal hazards and risks. A static raster map of coastal morphology was generated for the entire South American continent. The validation work was completed using OpenStreetMap coastline information and freely available Landsat satellite images in Google’s Earth Engine (https://explorer.earthengine.google.com). The following steps were taken: - The OpenStreetMap “coastline” tagged data was downloaded for South America - The coastline dataset was buffered in order to define the spatial extents of the analysis - The long-term coastal morphology was defined in this buffered zone as: # The difference in water masks (i.e. the normalized water difference index, NDWI) between the historic and present satellite images # The historic images represent the average mosaic cloud-free image from the 1980s using both the Landsat 4 and 5 satellites (due to lack of temporal coverage) # The present images represent the average mosaic cloud-free image from the Landsat 8 satellite (began its mission in 2013)

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