<abstract xmlns="http://www.w3.org/1999/xhtml"><p>As new information is received, predictions of sea-level rise resulting from global warming continue to be revised upwards. Measurements indicate that the rise in sea-level is continuing at, or close to, the worst case forecasts (Kellet et al. 2014). Coastal areas are coming under increasing risk of inundation and flooding as storms are predicted to increase in frequency and severity, adding to the risk of inundation due to higher sea levels. Stakeholders, government agencies, developers and land owners require accurate, up to date information to be able to protect coastal areas. Geographic Information Systems (GIS) along with accurate remote sensing technologies such as LiDAR provides the best means for delivering this information. Using these technologies, this paper predicts the risk posed to a large multi-use development in the emirate of Ras Al Khaimah, UAE. This development, Al Hamra Village, is situated on the coast of the Arabian Gulf. Al Hamra’s physical relationship to the Gulf is in common with other developments in Ras Al Khaimah in its and for this reason has been used as a pilot project. The resulting GIS model shows that Al Hamra is indeed at risk from predicted flood events. How this information can be used as a planning tool for numerous strategies is discussed in this paper.</p></abstract>

As new information is received, predictions of sea-level rise resulting from global warming continue to be revised upwards. Measurements indicate that the rise in sea-level is continuing at, or close to, the worst case forecasts (Kellet et al. 2014). Coastal areas are coming under increasing risk of inundation and flooding as storms are predicted to increase in frequency and severity, adding to the risk of inundation due to higher sea levels. Stakeholders, government agencies, developers and land owners require accurate, up to date information to be able to protect coastal areas. Geographic Information Systems (GIS) along with accurate remote sensing technologies such as LiDAR provides the best means for delivering this information. Using these technologies, this paper predicts the risk posed to a large multi-use development in the emirate of Ras Al Khaimah, UAE. This development, Al Hamra Village, is situated on the coast of the Arabian Gulf. Al Hamra’s physical relationship to the Gulf is in common with other developments in Ras Al Khaimah in its and for this reason has been used as a pilot project. The resulting GIS model shows that Al Hamra is indeed at risk from predicted flood events. How this information can be used as a planning tool for numerous strategies is discussed in this paper.

<bold>Predicting the Extent</bold> of Inundation due to Sea-Level Rise: Al Hamra Development, Ras Al Khaimah, UAE. A Pilot Project

The American University of Ras Al Khaimah, UAE

Independent Coastal Management Consultant, South Africa

Miscellanea Geographica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

 of Inundation due to Sea-Level Rise: Al Hamra Development, Ras Al Khaimah, UAE. A Pilot Project

As new information is received, predictions of sea-level rise resulting from global warming continue to be revised upwards. Measurements indicate that the rise...

Predicting the Extent of Inundation due to Sea-Level Rise: Al Hamra Development, Ras Al Khaimah, UAE. A Pilot Project

Published Online: Jun 16, 2016

Page range: 25 - 31

Received: Mar 20, 2015

Accepted: Mar 16, 2016

DOI: https://doi.org/10.1515/mgrsd-2016-0012

Keywords
Sea Level Rise, GIS, LiDAR

© 2016 Robert M. Arthur et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Predicting the Extent of Inundation due to Sea-Level Rise: Al Hamra Development, Ras Al Khaimah, UAE. A Pilot Project

Published Online: Jun 16, 2016

Page range: 25 - 31

Received: Mar 20, 2015

Accepted: Mar 16, 2016

DOI: https://doi.org/10.1515/mgrsd-2016-0012

KeywordsSea Level Rise, GIS, LiDAR

© 2016 Robert M. Arthur et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
Sea Level Rise, GIS, LiDAR