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Lunenburg Part 2 - Section 5 - Social Vulnerability - August 30.pdf

Lunenburg Part 2 - Section 5 - Social Vulnerability - August 30.pdf

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indicate the indicators of greatest vulnerability. Radar charts provide an easily understood<br />

representation of complex information about a particular dissemination area, so that the needs of<br />

that area can be better understood. 20<br />

Figure 1: Sample Radar Chart<br />

Data Interpretation: Synthesis<br />

The final step in the mapping procedure was to overlay the mapped information from the index<br />

of social vulnerability with sea level rise and storm surge scenario maps generated in a previous<br />

ACAS study (see <strong>Part</strong> 2, <strong>Section</strong> 1 of this report). This demonstrates the intersection of social<br />

vulnerability with anticipated climate change impacts.<br />

Interpretation involved counting both the number of residential buildings, and number of services<br />

that socially vulnerable people rely on, that would be either inundated or isolated (areas<br />

surrounded by water, or where the only road access is flooded) in each scenario. Some studies<br />

attempt to mathematically combine data about physical impacts with data from the index of<br />

social vulnerability, to obtain a numeric representation of overall vulnerability. This process<br />

involves assigning a numeric weight to different flood impacts (such as a value of 1 for buildings<br />

inundated and a value of 0.5 for buildings isolated). However, the choice of weightings and<br />

method for combining the data is highly subjective, and can cause very significant differences in<br />

the results obtained. Instead, this study uses a qualitative approach to interpreting the extent of<br />

physical impacts in light of the degree of social vulnerability in each dissemination area.<br />

The mapping component of this project was carried out using a Geographic Information System<br />

(ArcGIS). GIS is a widely-used mapping and geospatial analysis tool used by many<br />

municipalities, including the District of <strong>Lunenburg</strong>. The municipality has an existing database of<br />

GIS data for features such road networks, infrastructure and dwellings. Additionally, Light<br />

Detection and Ranging (LiDAR) data, which provides a highly accurate GIS-compatible map of<br />

the study area, was available for most areas of the District of <strong>Lunenburg</strong>. Finally, the ACAS sea<br />

level rise and storm surge scenarios were also generated in GIS.<br />

However, this mapping and overlay procedure could easily be carried out using other means –<br />

either through the use of graphic software capable of displaying layers of information, such as<br />

the Adobe Creative Suite, or manually. While skilled draftspersons can create hand-generated<br />

20 Wall and Marzall, 2006. p. 388<br />

8

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