Satellite precipitation–based extreme event detection for flood index insurance
نویسندگان
چکیده
This paper introduces a novel Satellite Precipitation-based Extreme Event Detection (SPEED) model to effectively support parametric or index insurance instruments specifically designed cover flood risk. Such financial tools are intended promote fast payouts in the aftermath of disastrous event. They leverage on measured hazard parameters, gathered immediately after event and defined as trigger(s), which used identify such hazardous events estimate their resulting consequences terms physical damage losses. addresses first step modeling approach, detection event, plays an important role overall methodology, determining its performance false missed detections. Different types triggers for identifying events, based satellite precipitation estimates, investigated, is assessed case-study country (the Philippines). A statistical procedure selecting optimal configuration parameters presented. minimizes so-called basis risk, this study mismatch between modeled actual events. Finally, accuracy proposed approach localization investigated by subdividing into three main areas, corresponding coarsest administrative levels, assessing model's capability capture each considered area. The results from confirm that SPEED can be input products, given ability correctly.
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ژورنال
عنوان ژورنال: International journal of disaster risk reduction
سال: 2021
ISSN: ['2212-4209']
DOI: https://doi.org/10.1016/j.ijdrr.2021.102108