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Published August 2, 2023 | Version 1.0
Dataset Open

Global database of Coastal Characteristics (GCC)

Creators

  • 1. Deltares
  • 2. Climate Change and Sustainable Development Department, Asian Development Bank
  • 3. Department of Marine Sciences, University of the Aegean
  • 4. Department of Coastal and Urban Risk & Resilience, IHE Delft Institute for Water Education

Description

This dataset present a Global database of Coastal Characteristics (GCC) with 80 indicators spanning the

  • geophysical,
  • hydrometeorological and
  • socioeconomic

environment, at a high alongshore resolution of 1 km and provided at ~730,000 points along the global ice-free coastline. The latest freely available global datasets and a global high-resolution transect system are used to derive these indicators.

The geophysical indicators include coastal slopes and elevation maxima, land-use, presence of vegetation or sandy beaches.The hydro-meteorological indicators involve water level, wave conditions and meteorological conditions (rain and temperature). Additionally, the socioeconomic indices are related to population, GDP and presence of critical infrastructure (roads, railways, ports and airports).

The indicators are provided in three comma-separated values (CSV) files, one for each group:

  • GCC_geophysical.csv
  • GCC_hydrometeorological.csv
  • GCC_socioeconomic.csv

Information for each individual indicator, including its name, long name (description), units and type, are provided in the meta_data.yml file.

Notes

While derived from existing global datasets, these indicators can be valuable for coastal screening studies, especially for data-poor locations. However, since the indicators are based on global data, the developed indicators of the GCC dataset should not be seen as a replacement for local-scale studies or data-collection and monitoring campaigns and should not be directly employed for very local scale efforts such as, for e.g., designing coastal adaptation measures or informing decision making.

Files

GCC_geophysical.csv

Files (435.2 MB)

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Additional details

Related works

Is described by
Preprint: 10.5194/essd-2023-313 (DOI)