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Case Study

Disaster Recovery

Geospatial intelligence and consequence models gave city leaders system-level visibility across ~19,000 structures in the wake of a fatal tornado.
Structures assessed
0
Damaged buildings
0
Severely damaged
0
Losses prioritized
~$ 0 B

The Challenge

Following a tornado causing fatalities, dozens of injuries, and displacement across multiple neighborhoods, city leaders faced urgent decisions across ~19,000 structures with limited real-time visibility. Fragmented data slowed assessment of ~5,400 damaged buildings and prioritization of response resources across affected wards.

SandOS in Action

Geospatial intelligence integrated satellite imagery, infrastructure data, and property records to classify damage severity at parcel level across ~19,000 structures. Scenario models identified priority response zones, highlighting ~3,000 severely damaged buildings concentrated across key wards, informing coordinated recovery and resource allocation decisions.

The Impact

City teams gained system-level visibility into ~5,400 damaged structures and ~$0.8B in estimated losses, enabling prioritization of the most affected neighborhoods first. Coordinated response improved allocation of shelter, medical, and recovery resources across neighborhoods with the highest concentration of severe damage.

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