After a flood or a fire, the first question is which of your locations are affected and how badly. Satellites can answer much of it within days; the work is getting that answer onto your own portfolio.
All Space & Earth Observation →
Satellite flood mapping uses radar and optical imagery to outline where water is after an event; the same approach maps burn scars after wildfire and damage after storms. Overlaid on an insurer’s or lender’s exposure, those layers become geospatial risk signals: which insured locations are likely affected, and which need a person to look first.
Radar is the workhorse because floods come with cloud, and Sentinel-1 sees through it. Public rapid-mapping services such as the Copernicus Emergency Management Service publish event maps for major disasters; the gap is joining them, and your own analysis, to your policies or assets quickly and consistently. These signals complement a catastrophe model, they do not replace one, and a claims handler or underwriter makes every decision.
flood · fire · storm
radar first, optical when clear
with confidence and dates
your geocoded locations
ranked list with imagery
flagged for field or desk review
Radar satellites such as Sentinel-1 send microwave pulses that bounce away from smooth water and back from rough land, so open flood water appears dark and stands out from its surroundings, through cloud and at night. Comparing an image during the flood with one from before separates flooding from permanent water. Optical imagery adds detail when the sky clears. Urban and vegetated areas are harder and need extra care.
After an event, to see which insured locations are likely affected and prioritise claims handling and loss estimates. Before an event, as inputs on historical hazard and exposure for underwriting and accumulation management. In parametric cover, a measured index can trigger a payout under the policy terms. In every case the data informs a decision a person or a contract makes.
No. A catastrophe model simulates many possible events to estimate loss probabilities; satellite signals describe events that have happened and conditions on the ground. They are complementary: observed footprints can help calibrate or check a model, and model output shapes where to look. Your modelling team decides how, and whether, to combine them.
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Bring a past event and a sample of your exposure. We will show how quickly the affected list could have been drawn.
30-minute technical call · no deck