Coastal vulnerability Index (CVI), is one of the predictive approaches to coastal classification by incorporating various coastal variables. This approach is favoured in the coastal investigation as it simplifies a number of complex parameters. However, it comes greatly as to why such assessment is developed in the first place; a) to facilitate coastal management in recent coastal condition, b) to classify potential shoreline responses to future sea-level rise, and c) for management of data storage. Index development in coastal investigation is one of the present-day technique used to estimate the vulnerability of the coast and is affected by a diverse range of variables. The widespread use of contemporary technology nowadays has led to a favourable coastal component to be considered in determining coastal vulnerability and environmental risk analysis. Therefore, it must be guided by acknowledging appropriate data to be used at spatial scale of interest, the geomorphology of the area concerns and etc. USA and European countries like Northern Ireland are one of the forefront country in addressing the significance of CVI in protecting coastal area. A stepwise approach to development of CVI is discussed in detail in this paper. Besides, the potential of including coastal components based on special characteristic at particular coasts for coastal vulnerability analysis are also reviewed. CVI eventually will assist coastal communities in providing guidance for mitigation of coastal threats in future urban development.

This paper presents the Coastal Altimetry Waveform Retracking Expert System (CAWRES), a novel method to optimise the Jason satellite altimetric sea levels from multiple retracking solutions. CAWRES’ aim is to achieve the highest possible accuracy of coastal sea levels, thus bringing measurement of radar altimetry data closer to the coast. The principles of CAWRES are twofold. The first is to reprocess altimeter waveforms using the optimal retracker, which is sought based on the analysis from a fuzzy expert system. The second is to minimise the relative offset in the retrieved sea levels caused by switching from one retracker to another using a neural network. The innovative system is validated against geoid height and tide gauges in the Great Barrier Reef, Australia for Jason-1 and Jason-2 satellite missions. The regional investigations have demonstrated that the CAWRES can effectively enhance the quality of 20 Hz sea level data and recover up to 16% more data than the standard MLE4 retracker over the tested region. Comparison against tide gauge indicates that the CAWRES sea levels are more reliable than those of Sensor Geophysical Data Records (SGDR) products, because the former has a higher (≥0.77) temporal correlation and smaller (≤19 cm) root mean square errors. The results demonstrate that the CAWRES can be applied to coastal regions elsewhere as well as other satellite altimeter missions.