Empirical estimation based on remote sensing images of insured typhoon-induced economic losses from building damage

Rapid and cost-effective economic loss estimation for buildings in non-life insurance is an impor-tant issue for insurance industries in order to provide immediate financial supports to residents affected by natural disasters. This study introduces an empirical approach for economic loss esti-mation of typhoon-induced building damage from post-disaster remote sensing (RS) images based on insurance records obtained in Osaka and Chiba, Japan affected by the 2018 Typhoon Jebi and the 2019 Typhoon Faxai, respectively. From the insurance records and the analysis of the RS images, we found that area-based loss rates (ALRs) defined as ratio of amount of loss to amount of insured values within a mesh were proportional to building damage ratios (BDRs) identified from number of damaged buildings in the RS images and existing building inventory data, whereas it was still challenging to accurately estimate loss rate for building-by-building even from very high-resolution images. A linear regression function was developed from the rela-tionship between the ALRs and BDRs obtained in this study. We confirmed that the regression function provided a good approximation of the insured losses from the typhoon disasters. The re-sult indicates that typhoon-induced insured losses can be rapidly estimated from the insurance in-ventory and the analysis of post-disaster RS images without field investigations.