Global Coastal Characteristics (GCC): A global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators
Abstract. Around 10 percent of the world's population live in coastal areas that are less than 10 meters above sea level (also known as the low elevation coastal zone – LECZ). Coastal zones are therefore of major importance for local economy, transport and are home to some of the richest ecosystems. This makes coastal zones quite susceptible to extreme storms and sea level rise due to climate change. During the last few years numerous open access global datasets have been published, describing different aspects of the environment such as elevation, land-use, waves, water-levels and exposure. However, for coastal studies it is crucial that this information is available at specific coastal locations and, for regional studies or upscaling purposes, it is also important that data is provided in a spatially consistent manner. Here we create a Global database of Coastal Characteristics (GCC) with 80 indicators covering 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. To achieve this, we use the latest freely available global datasets and a newly created global high-resolution transect system. 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, socioeconomic indices related to population, GDP and presence of critical infrastructure (roads, railways, ports and airports) are presented. While derived from existing global datasets, these indicators can be valuable for coastal screening studies, especially for data-poor locations.
Status: open (until 27 Mar 2024)
Global Coastal Characteristics (GCC): A global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators https://doi.org/10.5281/zenodo.8200200
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