EGU22-5942
https://doi.org/10.5194/egusphere-egu22-5942
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

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

James Brennan, Claire Burke, Laura Ramsamy, Hamish Mitchell, and Kamil Kluza
James Brennan et al.
  • Climate X, London, United Kingdom (james.brennan@climate-x.com)
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).

How to cite: Brennan, J., Burke, C., Ramsamy, L., Mitchell, H., and Kluza, K.: Using remote sensing and GIS to project climate risk for asset management users, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5942, https://doi.org/10.5194/egusphere-egu22-5942, 2022.