Product description: TF_Winter_dsm.zip Type: Drone-derived DSM Date of survey: 20170217 Personnel: BRE, EKC, IM, MS, HB Coverage: Area surrounding wave logging trasect and survey quadrats at Tillingham, UK Platform: DJI Matrice 100 Camera: Zenmuse X5 GCP survey equipment: Leica GS08 RTK GPS GCP locational accuracy: X:0.02m, Y:0.02m, Z:0.02m Average GSD: 1.66cm Processing report: tf_20170217_zenmuse_report.pdf

Product description: DN_Winter_DSM_Corr1.tif Drone-derived DSM Date of survey: 20170220 Personnel: BRE, EKC, IM, MS Coverage: Area surrounding wave logging transport and survey quadrats at Donna Nook, UK Platform: DJI Matrice 100 Camera: Zenmuse X5 GCP survey equipment: Leica GS08 RTK GPS GCP locational accuracy: X:0.02m, Y:0.02m, Z:0.02m Average GSD: 1.66cm Processing report: dn_20170220_zenmuse_report.pdf

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)

LIDAR Composite Digital Terrain Model (DTM) downloaded from environment.data.gov.uk, styled and converted into WMS/WCS for use in the FAST expert version.

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

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 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 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