# Urban Vulnerability Assessment of Sea Level Rise in Singapore through the World Avatar
## 4 Use Case  
### Impact Assessment and Integrated Spatial Planning  
By combining the results of the OSM agent, the building floor agent, the GFA agent, the cost agent, and the sea level impact agent, TWA provides a multi-scale approach to vulnerability assessment, offering both comprehensive and granular insights. In Figure 3, we demonstrate one of the extreme scenarios based on the SSP5-8.5 low-confidence scenario in the year 2150 with a 6.0 m sea level rise. In the figure, TWA enables a broad, country-level assessment of vulnerabilities of various aspects including buildings, road networks, land plots, cultural sites, and population. Additionally, TWA is also capable of detailed, site-specific evaluations as shown in Figure 4. By integrating diverse datasets into a unified visualisation platform, TWA supports both extensive country-wide assessments and detailed vulnerability assessments. The results shown in the figures are influenced by the quality of the input elevation model and sea level rise model. The input model--NASA SRTM elevation model--was taken in the year 2000 and does not capture the recent land reclamation in the southwest region of the island that happened after, and therefore the results should be interpreted with caution. However, this limitation does not undermine the objective and results presented in this paper. The intention is to demonstrate the TWA as a proof of concept for sea level rise vulnerability assessment. Should a more accurate elevation model become available, the methodology would remain valid with the updated elevation model that would be substituted. Figure 3: Impact overview of the SSP5-8.5 low-confidence scenario in the year 2150 at the 95 th percentage quantile with a 6.0 m sea level rise. The figures designate the low-lying vulnerable areas,  
particularly on the southwestern side (Tues) and the eastern side (Changi) of Singapore due to land reclamation after the SRTM elevation data were recorded. This result can be improved by using a more recent and accurate elevation model for TWA. (**a**) Singapore. (**b**) Vulnerable Singapore. (**c**) Vulnerable buildings. (**d**) Vulnerable road network breakdown by road types. (**e**) Vulnerable land plot with designated usages. (**f**) Vulnerable cultural sites. (**g**) Vulnerable population distribution. The country-wide vulnerable area visualisation enables planners to identify and prioritise areas that are more heavily affected by potential sea level rise. It serves as a decision support tool to guide and assist planners in making informed decisions. The combination of multiple data such as buildings, road networks, land, cultural sites, and population distribution provides a better birds-eye perspective, creating a more comprehensive insight representation. The semantic representation behind each of the datasets described using  
Figure 4: Vulnerable buildings based on SSP5-8.5 low-confidence scenario in the year 2150 with a 6.0 m sea level rise. (**a**) Vulnerable buildings by property usage. (**b**) Vulnerable buildings by estimated construction cost. ontologies (i.e., OntoSeaLevel, OntoBuiltEnv, OntoPlot, OntoZone, OpenStreetMap Ontology) provides an in-depth representation of attributes beyond basic GIS representation. The representation of sea level projections and their impacted sites (i.e., buildings, road network, land plot, cultural sites) using ontologies enables the querying of various insights that are relevant to sea level rise risk mitigation such as the populations at risk for a specific sea level rise projection scenario, the type of property usage and its estimated construction cost for the vulnerable buildings, the type of land plot, and the area affected by a specific sea level rise projection scenario. The combination of country-wide visualisation support and the use of ontologies for information representation allows for a more precise depiction of datasets.