Researchers are continually faced with the challenge of integrating large volumes of complex ecological and environmental data sets. Typically the spatial and temporal components of data sets are underutilised as methods for adequately handling such data are not readily available. Eonfusion is a new four-dimensional (4D) visualisation and analysis software package which significantly enhances the ease with which scientists can integrate and explore complex spatially and temporally variant data sets. In this case study we developed two models to predict the impact of rising sea levels to low-lying coastal areas using a suburb of Hobart as an example. The spatio-temporal inundation model enabled the effective visualization of sea level rise scenarios to assess the extent and impact of inundation. The model was produced using publically available LiDAR data, obtained from the Antarctic and Climate Ecosystems CRC - Climate Futures Project, and sea level scenarios published by the Intergovernmental Panel on Climate Change (IPCC). The second model integrated geomorphic coastal vulnerability mapping and the IPCC sea level scenarios to examine the impact of rising sea levels to the erosion of coastal areas. This case study will highlight the power of Eonfusion for the efficient and effective integration of inundation and vulnerability models and demonstrate the universal application of the software to the field of climate change research.