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Information about shoreline evolution trend has influenced coastal policy formulation and enabled development of sustainable coastal management practices worldwide. Numerous studies have reported varied rates of change ranging between 1.5 and 15 m/yr in Ghana's Accra shoreline, a data starved nation. This has resulted in the lack of effective and sustainable management of the coastal resources. The study reported in this book addresses this issue using mapping data from 1904, 1974, 1996 and 2002 to estimate shoreline recession in the Accra region. Predictions for the next 250 yr were then…mehr

Produktbeschreibung
Information about shoreline evolution trend has influenced coastal policy formulation and enabled development of sustainable coastal management practices worldwide. Numerous studies have reported varied rates of change ranging between 1.5 and 15 m/yr in Ghana's Accra shoreline, a data starved nation. This has resulted in the lack of effective and sustainable management of the coastal resources. The study reported in this book addresses this issue using mapping data from 1904, 1974, 1996 and 2002 to estimate shoreline recession in the Accra region. Predictions for the next 250 yr were then undertaken using a variety of modelling techniques and accounting for uncertainties. The rate of erosion in the Accra region was found to be 1.13 m/yr (±0.17 m/yr). Subsequent predictions were used to identify a series of significant economic, ecological and social features at risk, and to estimate when they will most likely be lost to erosion if left unprotected. The study illustrates that it is possible to provide reliable statistical information in support of sustainable coastal management for developing countries in the face of a changing climate.
Autorenporträt
Appeaning Addo holds a PhD degree in Geomatic Engineering from the Newcastle University, UK. He is a lecturer at the Accra Polytechnic and the University of Ghana, and a member of the Ghana Institution of Engineers. His research interest is in the quantification of regional scale coastal erosion in a data-sparse environment.