• DOI:10.1006/ECSS.1999.0507
• Corpus ID: 128982465

The Relative Lengths of Seashore Substrata Around the Coastline of Ireland as Determined by Digital Methods in a Geographical Information System

@article{Neilson1999TheRL,
  title={The Relative Lengths of Seashore Substrata Around the Coastline of Ireland as Determined by Digital Methods in a Geographical Information System},
  author={Brigitte Neilson and Mark John Costello},
  journal={Estuarine Coastal and Shelf Science},
  year={1999},
  volume={49},
  pages={501-508}
}

• B. Neilson, Mark John Costello
• Published 1 October 1999
• Environmental Science
• Estuarine Coastal and Shelf Science

Coastal zone management requires standardized and quantitative information on the distribution of natural habitats. For example, the European Union Habitats Directive requires member states to protect habitats in relation to their proportion within that state's territory. Basic information on sea-bed types is available on marine charts. However, gaining an overview of, or analysing patterns within it, is difficult because of the many charts at different scales and projections. In this paper a methodology is described using a geographical information system (GIS), by which the high tide mark of Ireland was labelled with the dominant sea-bed types. The counties with the longest coastlines are Cork, Mayo, Donegal, Galway, Kerry and Clare. They have the most mud, sand, gravel, rocks, cliff and marsh respectively. The 7524 km coastline is 41% rock, 34% sand and 11% mud. How the statistics are derived can provide a basis for comparison between coastal areas at both a national (e.g. islands vs mainland, between counties) and international (e.g. comparison with coasts of France) level and be used to extrapolate the amount of natural resources and predict how much time field surveys would take, is demonstrated. This approach is applicable to any coastal area for which basic seabed information exists. It can be analysed for management and research purposes and provides a baseline on which additional datasets may be added (e.g. climate, bathymetry, tides, natural resources, conservation importance) to produce a GIS of greater value than the sum of its parts.