The Murray Global Tidal Wetland Change Dataset contains maps of the global extent of tidal wetlands and their change. The maps were developed from a three stage classification that sought to (i) estimate the global distribution of tidal wetlands (defined as either tidal marsh, tidal flat or mangrove ecosystems), (ii) detect their change over the study period, and (iii) estimate the ecosystem type and timing of tidal wetland change events.

The original World Vector Shoreline (WVS) was a digital data file containing the shorelines, international boundaries, and country names of the world. WVS data were processed into NGA’s Vector Product Format in 1995, resulting in the highest resolution demarcation of coastline globally available, the World Vector Shoreline Plus.

The Murray Global Tidal Wetland Change Dataset contains maps of the global extent of tidal wetlands and their change. The maps were developed from a three stage classification that sought to (i) estimate the global distribution of tidal wetlands (defined as either tidal marsh, tidal flat or mangrove ecosystems), (ii) detect their change over the study period, and (iii) estimate the ecosystem type and timing of tidal wetland change events.

The ASTER Global Digital Elevation Model (GDEM) Version 3 (ASTGTM) provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).

This dataset provides a complete rainfall erosivity dataset for the whole World based on 3,625 precipitation stations and around 60,000 years of rainfall records at high temporal resolution (1 to 60 minutes). Gaussian Process Regression(GPR) model was used to interpolate the rainfall erosivity values of single stations and to generate the R-factor map.

The GRDC is an international archive of data up to 200 years old, and fosters multinational and global long-term hydrological studies. Originally established three decades ago, the aim of the GRDC is to help earth scientists analyse global climate trends and assess environmental impacts and risks. Operating under the auspices of WMO the database of quality controlled “historical” mean daily and monthly discharge data grows steadily and currently comprises river discharge data of well over 10,000 stations from 159 countries.

This dataset includes global soil salinity layers for the years 1986, 1992, 2000, 2002, 2005, 2009 and 2016. The maps were generated with a random forest classifier that was trained using seven soil properties maps, thermal infrared imagery and the ECe point data from the WoSIS database.

FABDEM (Forest And Buildings removed Copernicus DEM) is a global elevation map that removes building and tree height biases from the Copernicus GLO 30 Digital Elevation Model (DEM). The data is available at 1 arc second grid spacing (approximately 30m at the equator) for the globe.