The use of unmanned aerial vehicles to estimate direct tangible losses to residential properties from flood events: A case study of Cockermouth following the Desmond storm - Rivas Casado, Monica; Irvine, Tracy; Johnson, Sarah; Palma, Marco; Leinster, Paul (Cranfield University, 2018)
Damage caused by flood events is expected to increase in the coming decades driven by increased land use pressures and climate change impacts. The insurance sector needs accurate and efficient loss adjustment methodologies for flood events. These can include remote sensing approaches that enable the rapid estimation of (i) damage caused to property as well as (ii) the number of affected properties. Approaches based on traditional remote sensing methods have limitations associated with low-cloud cover presence, oblique viewing angles, and the resolution of the geomatic products obtained. Unmanned aerial vehicles (UAVs) are emerging as a potential tool for post-event assessment and provide a means of overcoming the limitations listed above. This paper presents a UAV-based loss-adjustment framework for the estimation of direct tangible losses to residential properties affected by flooding. For that purpose, features indicating damage to property were mapped from UAV imagery collected after the Desmond storm (5 and 6 December 2015) over Cockermouth (Cumbria, UK). Results showed that the proposed framework provided an accuracy of 84% in the detection of direct tangible losses compared with on-the-ground household-by-household assessment approaches. Results also demonstrated the importance of pluvial and, from eye witness reports, lateral flow flooding, with a total of 168 properties identified as flooded falling outside the fluvial flood extent. The direct tangible losses associated with these additional properties amounted to as high as £3.6 million. The damage-reducing benefits of resistance measures were also calculated and amounted to around £4 million. Differences in direct tangible losses estimated using the proposed UAV approach and the more classic loss-adjustment methods relying on the fluvial flood extent was around £1 million—the UAV approach providing the higher estimate. Overall, the study showed that the proposed UAV approach could make a significant contribution to improving the estimation of the costs associated with urban flooding, and responses to flooding events, at national and international levels.
Keywords: drone; unmanned aerial vehicle; flood; catastrophe; impact; extent; damage; identification