Which statement describes hot spot analysis in risk management most accurately?

• A. Hot spot analysis uses Getis-Ord Gi* to identify clusters of high-risk values.
• B. Hot spot analysis eliminates all risk immediately.
• C. Hot spot analysis is a qualitative, non-spatial method.
• D. Hot spot analysis only applies to weather data.

Answer: (A)

Hot spot analysis in risk management is about detecting where risk values cluster in space, turning patterns into actionable priorities. A standard way to do this is by using a local statistic such as Getis-Ord Gi*, which for each location assesses whether nearby values co-occur at higher (or lower) levels than expected. It computes a z-score that signals a statistically significant hot spot (high-risk cluster) or cold spot. This makes hot spot analysis a precise, quantitative spatial method rather than a qualitative one. It also doesn't imply risk is removed by the analysis; it simply identifies where effort should be concentrated. Moreover, it's not limited to weather data—it can be applied to any geospatial risk metric. Therefore, the description that hot spot analysis uses Getis-Ord Gi* to identify clusters of high-risk values is the most accurate.