Using remote sensing and GIS to project climate risk for asset management users

At Climate X we are producing risk estimates for the UK to help businesses and communities mitigate and adapt for climate change related losses. Climate X provides risk scores and expected financial losses from a plethora of hazards including flooding, subsidence, landslides, drought, fire and extreme heat. To do this at the scales we need, Earth Observation (EO) and other geospatial data sets play a crucial role in both physical modelling and risk estimation. Generating rich geospatial datasets to sit as the bedrock of risk models requires intelligent use of multiple data sources, involving the fusion of EO data from synthetic aperture radar, lidar and optical instruments and across processing levels from L1 to L3. This talk will cover the generation and use of these datasets that drive physical risk models (flooding) as well as ML enabled models (Landslides and subsidence).