A new global coastal database for impact and vulnerability analysis to sea-level rise.

Vafeidis, Athanasios T. and Nichols, Robert J. and McFadden, Loraine and Tol, Richard S. J. and Hinkel, Jochen and Spencer, Tom and Grashoff, Paul .S. and Boot, Gerben and Klein, Richard J. T. (2008) A new global coastal database for impact and vulnerability analysis to sea-level rise. Journal of Coastal Research, 24 (4). pp. 917-924. ISSN 0749-0208

Full text is not in this repository.

Official URL: http://jcronline.org/doi/full/10.2112/06-0725.1

Abstract

A new global coastal database has been developed within the context of the DINAS-COAST project. The database covers the world's coasts, excluding Antarctica, and includes information on more than 80 physical, ecological, and socioeconomic parameters of the coastal zone. The database provides the base data for the Dynamic Interactive Vulnerability Assessment modelling tool that the DINAS-COAST project has produced. In order to comply with the requirements of the modelling tool, it is based on a data model in which all information is referenced to more than 12,000 linear coastal segments of variable length. For efficiency of data storage, six other geographic features (administrative units, countries, rivers, tidal basins or estuaries, world heritage sites, and climate grid cells) are used to reference some data, but all are linked to the linear segment structure. This fundamental linear data structure is unique for a global database and represents an efficient solution to the problem of representing and storing coastal data. The database has been specifically designed to support impact and vulnerability analysis to sea-level rise at a range of scales up to global. Due to the structure, consistency, user-friendliness, and wealth of information in the database, it has potential wider application to analysis and modelling of the world's coasts, especially at regional to global scales.

Item Type:Article
Keywords (uncontrolled):: Segmentation, coastal geographic information system (GIS), data model, climate change, global change
Research Areas:School of Science and Technology > Natural Sciences
Citations on ISI Web of Science:20
ID Code:4980
Useful Links:
Deposited On:19 Apr 2010 09:49
Last Modified:13 May 2014 15:50

Repository staff and depositor only: item control page

Full text downloads (NB count will be zero if no full text documents are attached to the record)

Downloads per month over the past year