Describe a basic geospatial risk assessment workflow for a new manufacturing site.

• A. Build a 3D model of the site with no risk context.
• B. Define purpose and scope; collect locations; overlay hazard layers; estimate exposure and vulnerability; compute risk scores; run scenario analyses; identify mitigations and monitoring plan.
• C. Only collect hazard layers and skip risk scoring.
• D. Conduct financial audit without spatial data.

Answer: (B)

The main idea is that a geospatial risk assessment for a new manufacturing site follows a structured flow from purpose to actionable outcomes. Start by defining why you’re assessing risk and what assets, operations, and time horizon matter. Then gather spatial data on locations and assets and bring in hazard information such as flood zones, seismic data, wildfire risk, severe weather, industrial accidents, and climate projections, plus critical infrastructure. Overlay these hazard layers with asset locations so you can see where hazards intersect with what needs protection, creating a spatial picture of exposure.

Next, translate that exposure into a risk measure by considering vulnerability—how well assets and people can withstand or recover from impacts—and how likely the hazards are. This gives you a risk score or map that prioritizes which areas or assets are most at risk. Running scenario analyses is the step that tests how risk changes under different conditions, like more intense storms, higher flood depths, or supply-chain disruptions, helping you plan for uncertainty and climate change.

Finally, use the insights to identify mitigations and a monitoring plan. That means selecting concrete controls (design changes, storage practices, site layout, redundancy, early warning, and response plans) and setting up indicators to track risk over time so the site remains resilient.

Context helps make this concrete: mapping a site near a floodplain would show where exposure is highest and guide decisions about flood defenses, material storage away from risky zones, and monitoring triggers. The other options don’t provide the full picture: a 3D model without risk context doesn’t show potential impacts; collecting hazard layers without scoring misses how likely and severe the impacts are; and a financial audit without spatial data ignores the geographic dimension of risk.