From 1 - 10 / 91
  • 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

  • Vegetation presence Paulinapolder 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 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

  • 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)

  • This is a reclassified product presenting a thematic subset of the European CORINE Land Cover (CLC) classes from CLC2012 within a 100 m grid for coastal situations. Corine Land Cover products are available in both raster (100 and 250 meter resolution), and vector (ESRI and SQLite geodatabase). The Minimum Mapping Unit (MMU) for the CLC is 25 hectares for areal phenomena and 100 meter for linear phenomena. The time series (1990, 2000, 2006 and 2012) are complemented by change layers, which highlight changes in land cover with an MMU of 5 ha. If you are interested in changes between two surveys always use the CLC-Change layer, as this has a higher resolution than the status layer. Results can be filtered by using the search box. Original file from http://land.copernicus.eu/pan-european/corine-land-cover/clc-2012

  • 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

  • Het Actueel Hoogtebestand Nederland (AHN) is een digitale hoogtekaart voor heel Nederland. Het bevat gedetailleerde en precieze hoogtegegevens met gemiddeld acht hoogtemetingen per vierkante meter. The Digital Elevation Model (AHN) of the Netherlands. AHN comprises detailed elevation with an averag of eight measurements per square meter.

  • This dataset contains bathymetry (depth) products from the compilation of all available source bathymetry data within the Great Barrier Reef into a 30 m-resolution Digital Elevation Model (DEM). The Great Barrier Reef (GBR) is the largest coral reef ecosystem on Earth and stretches over 2500 km along the north-eastern Australia margin. Bathymetry mapping of this extensive reef system is vital for the protection of the GBR allowing for the safe navigation of shipping and improved environmental management. Over the past ten years, deep-water multibeam surveys have revealed the highly complex shelf-edge drowned reefs and continental slope canyons. Airborne LiDAR bathymetry acquired by the Australian Hydrographic Service cover most of the GBR reefs, with coverage gaps supplemented by satellite derived bathymetry. The Geoscience Australia-developed Intertidal Elevation Model DEM improves the source data gap along Australia’s vast intertidal zone. All source bathymetry data were extensively edited as point clouds to remove noise, given a consistent WGS84 horizontal datum, and where possible, an approximate MSL vertical datum.

  • Vegetation presence Danube Delta based on L3A RapidEye data, image 1 June 2015,top of atmosphere radiance converted to surface reflectance and atmospheric correction using 6S, threshold NDVI=0. This is an unvalidated product for demo purposes only!For more information, please see EU FAST Internal Deliverable 3.8 (Example Geospatial products)