Nowcasting from space: Impact of tropical cyclones on Fiji's agriculture

The standard approach to 'nowcast' disaster impacts, which relies on risk models, does not typically account for the compounding impact of various hazard phenomena (e.g., wind and rainfall associated with tropical storms). The alternative, traditionally, has been a team of experts sent to the affected areas to conduct a ground survey, but this is time-consuming, difficult, and costly. Satellite imagery may provide an easily available and accurate data source to gauge disasters' specific impacts, which is both cheap, fast, and can account for compound and cascading effects. If accurate enough, it can potentially replace components of ground surveys altogether. An approach that has been calibrated with remote sensing imagery can also be used as a component in a nowcasting tool, to assess the impact of a cyclone, based only on its known trajectory, and even before post-event satellite imagery is available. We use one example to investigate the feasibility of this approach for nowcasting, and for post-disaster damage assessment. We focus on Fiji and on its agriculture sector, and on tropical cyclones (TCs). We link remote sensing data with available household surveys and the agricultural census data to obtain an improved assessment of TC impacts. We show that remote sensing data, when combined with pre-event socioeconomic and demographic data, can be used for both nowcasting and post-disaster damage assessments.