Modeling the effect of predicted sea-level rise on coastal conservation habitats using GIS

Global average temperatures have in creased by about 0.6°C (± 0.2°C) during the 20th century, and are project ed to increase by 1.4 - 5.8°C by 2100 (IPCC, 2001a). The relationship between atmospheric warming and sea-level rise (SLR) is well understood, and this change is predicted to lead to SLR of up to 1m by 2100, cr eating consequences for coastal communities and environments worldwide (IPCC, 2001b)

MSUO Information Technology and Geographical Information Systems: Common Protocols & Procedures. Report to the Marine Safety Umbrella Operation

The Marine Safety Umbrella Operation (MSUO) facilitates the cooperation between Interreg funded Marine Safety Projects and maritime stakeholders. The main aim of MSUO is to permit efficient operation of new projects through Project Cooperation Initiatives, these include the review of the common protocols and procedures for Information Technology (IT) and Geographical Information Systems (GIS). This study carried out by CSA Group and the National Centre for Geocomputation (NCG) reviews current spatial information standards in Europe and the data management methodologies associated with different marine safety projects. International best practice was reviewed based on the combined experience of spatial data research at NCG and initiatives in the US, Canada and the UK relating to marine security service information and acquisition and integration of large marine datasets for ocean management purposes. This report identifies the most appropriate international data management practices that could be adopted for future MSUO projects

Dual-frequency GPS survey for validation of a regional DTM and for the generation of local DTM data for sea-level rise modelling in an estuarine salt marsh

Global average temperatures have risen by an average of 0.07°C per decade over the last 100 years, with a warming trend of 0.13°C per decade over the last 50 years. Temperatures are predicted to rise by 2°C - 4.4°C by 2100 leading to global average sealevel rise (SLR) of 2 – 6mm per year (20 – 60cms in total) up to 2100 (IPCC 2007) with impacts for protected coastal habitats in Ireland. Estuaries are predominantly sedimentary environments, and are characterised by shallow coastal slope gradients, making them sensitive to even modest changes in sea-level. The Shannon estuary is the largest river estuary in Ireland and is designated as a Special Area of Conservation (SAC) under the EU Habitats Directive (EU 1992) providing protection for listed habitats within it, including estuarine salt marsh. Trends in Shannon estuary tidal data from 1877 – 2004 suggest an average upward SLR trend of 4 - 5mm/yr over this period. A simple linear extension of this historical trend would imply that local SLR will be in the region of 40 - 45cm by 2100. However, this may underestimate actual SLR for the estuary by 2100, since it takes no account of predicted climate-driven global SLR acceleration (IPCC 2007) up to 2100

Potential of INFOMAR Lidar Reflectivity in Seabed Characterisation: Statistical Assessment of Controls and Comparison with MBES Backscatter

The principal aim of this study was to assess the potential for INFOMAR LiDAR reflectivity data to be used for the classification of seabed characteristics. LiDAR bathymetry has been used successfully within the INFOMAR project for the generation of bathymetric charts, and the potential for LiDAR reflectivity for seabed mapping has begun to receive scientific attention elsewhere. INFOMAR has captured a huge amount of Multi-beam Echo Sounder (MBES) sonar data, and has successfully implemented techniques to classify seabed character from MBES backscatter data. This has provided an opportunity to compare LiDAR reflectivity data with that of MBES backscatter to assess the potential of LiDAR reflectivity for seabed characterisation

Potential of INFOMAR Lidar Reflectivity in Seabed Characterisation: Statistical Assessment of Controls and Comparison with MBES Backscatter

The principal aim of this study was to assess the potential for INFOMAR LiDAR reflectivity data to be used for the classification of seabed characteristics. LiDAR bathymetry has been used successfully within the INFOMAR project for the generation of bathymetric charts, and the potential for LiDAR reflectivity for seabed mapping has begun to receive scientific attention elsewhere. INFOMAR has captured a huge amount of Multi-beam Echo Sounder (MBES) sonar data, and has successfully implemented techniques to classify seabed character from MBES backscatter data. This has provided an opportunity to compare LiDAR reflectivity data with that of MBES backscatter to assess the potential of LiDAR reflectivity for seabed characterisation

Deprivation as an outcome determinant in emergency medical admissions

Background: Deprivation in the general population predicts mortality. We have investigated its relevance to an acute medical admission, using a database of all emergency admissions to St James’ Hospital, Dublin, over a ten year period (2002-2011). <p/>Methods: All emergency admissions, based on geocoding of residence, were allocated to a Small Area Health Research Unit (SAHRU) division, with a corresponding deprivation index. We then examined this index as a univariate (unadjusted) and independent (adjusted) predictor of 30-day in-hospital mortality. <p/>Results: The 30-day in-hospital mortality, over the 10 year period was higher, for those in the upper half of the deprivation distribution (9.6% vs 8.6%: p = 0.002). Indeed, there was a stepwise increase in 30-day mortality over the quintiles of deprivation from 7.3% (Quintile 1) to 8.8%, 10.0%, 10.0% and 9.3% respectively. Univariate logistic regression of the deprivation indices (quintiles) against outcome showed an increased risk (p = 0.002) of a 30-day death with OR’s respectively (compared with lowest deprivation quintile) of 1.23 (95% CI 1.07, 1.40), 1.41 (95% CI 1.24, 1.60), 1.41 (95% CI 1.24, 1.61) and 1.30 (95% CI 1.14, 1.48). The deprivation index was an independent predictor of outcome in a model when adjusted for illness severity and co-morbidity. The fully adjusted OR for a 30-day death was increased by 31% (p=0.001) for patients in the upper half of the deprivation index distribution (OR 1.31: 95% CI 1.20, 1.44). <p/>Conclusion: Deprivation independently of co-morbidity or acute illness severity is a powerful outcome predictor in acute medical admissions