Global Shallow-Water Seagrass Extent

This Seagrass/ Submerged Vegetation data layer is an ArcGIS shapefile layer covering only the Coastal inter-tidal zone of the Kenyan Indian Ocean waters. The layer product has been generated from Landsat-8 OLI Sensor data at 30 meter resolution utilizing the Blue, Green and Red Spectral bands for interpretation.

Retirement Notice: This item is in mature support as of December 2025 and will be retired in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version. Ocean depth plays an important role in the distribution and abundance of living organisms and has important implications for shipping and offshore development projects such as wind power and oil extraction. Phenomenon Mapped: Seafloor depth, bathymetryUnits: Meters below sea levelCell Size: 30 arc seconds, approximately 1 kmSource Type: DiscretePixel Type: Signed integerSpatial Reference: GCS_WGS_1984Mosaic Projection: Web Mercator Auxiliary SphereExtent: Global oceansSource: Marine Conservation Institute (MCI)Citation: Becker JJ, Sandwell DT, Smith WHF, Braud J, Binder B, et al. (2009) Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS. Marine Geodesy 32: 355–371.Publication Date: 2009ArcGIS Server URL: https://gis.earthdata.nasa.gov/portal/sharing/servers/3e20c8ae23b44ca7b99af621fdc129de/ The Marine Conservation Institute used this dataset as an input to a predictive habitat model documented in the publication Global Habitat Suitability for Framework-Forming Cold-Water Corals.  The source data is available from the Scripps Institution of Oceanography Satellite Geodesy Webpage. What can you do with this layer?  Visualization: This layer can be used for visualization online in web maps and in ArcGIS Desktop.  Analysis: This layer can be used as an input to geoprocessing tools and model builder.  Raster Functions: Unit Conversion – meters to feet, Cartographic Renderer, Aspect, Slope, and Hillshade - see this blog for more information.

__Note__: _A new version of this item is available for your use. This mature version of the map remains available for use in existing applications. This item will be retired in December 2024. There is 2020 data available in the newer 9-class dataset._ Global estimates of 10-class land use/land cover (LULC) for 2020, derived from ESA Sentinel-2 imagery at 10m resolution. This dataset was generated by Impact Observatory, who used billions of human-labeled pixels (curated by the National Geographic Society) to train a deep learning model for land classification. The global map was produced by applying this model to the relevant yearly Sentinel-2 scenes on the Planetary Computer. This dataset is also available on the ArcGIS Living Atlas of the World.

This dataset was generated within the framework of the Global Mangrove Watch (GMW), an initiative convened by Aberystwyth University, soloEO, The Nature Conservancy and Wetlands International. The larger dataset (v3.0) depicts the global extent of mangrove forests for the years 1996, 2007-2010, and 2015-2020, derived by L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA), thus developing a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. The classification was confined using a mangrove habitat mask, which defined regions where mangrove ecosystems can be expected to exist. The mangrove habitat definition was based on geographical parameters such as latitude, elevation and distance from ocean water. The habitat mask was initially developed in GMW v2.0 and has been revised in subsequent versions. Global coverage of mangroves for 2020

aircraft imagery by KFF, acquired 2026-03-05 to 2026-03-05, 3.6 cm per pixel, published on OpenAerialMap.

This data set was generated by Aberystwyth University and soloEO within the framework of the Global Mangrove Watch (GMW) project, which is a part of the Japan Aerospace Exploration Agency's (JAXA) Kyoto & Carbon Initiative and the Mangrove Capital Africa Programme coordinated by Wetlands International and financed by DOB Ecology. The map (v2.0) depicts the global extent of mangrove forests for the year 2010, derived by Random Forest Classification of a combination of L-band radar (ALOS PALSAR) and optical (Landsat-5, -7) satellite data. All satellite data and software used to derive the GMW mangrove maps are available in the public domain. Approximately 15,000 Landsat scenes and 1,500 ALOS PALSAR (1 x 1 degree) mosaic tiles were used to create optical and radar image composites covering the coastlines along the tropical and sub-tropical coastlines in the Americas, Africa, Asia and Oceania. The classification was confined using a mangrove habitat mask, which defined regions where mangrove ecosystems can be expected to exist. The mangrove habitat definition was based on geographical parameters such as latitude, elevation and distance from ocean water. Training for the habitat mask and classification of the 2010 mangrove mask was based on randomly sampling 38 million points using the mangrove masks (for the year 2000) of Giri et al. (2011) and Spalding et al. (2010) and the water occurrence layer defined by Pekel et al. (2017). The data set is available for download at http://data.unep-wcmc.org/datasets/45 Global coverage of mangroves for select years from 1996 to 2016