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Flooding affects more people than any other environmental hazard and hinders sustainable development1,2. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods3. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure5 and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty3,7–11. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255–290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58–86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates7. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods. Satellite imagery for the period 2000–2018 reveals that population growth was greater in flood-prone regions than elsewhere, thus exposing a greater proportion of the population to floods.

The measurement and recording of the height and spatial extent reached by coastal storm surges is fundamental to scientific progress in understanding these phenomena. Such information is required for better prediction and for risk assessment. Model-based evaluation of increasing delta vulnerability, for example, cannot be tested without long-term, consistent, and sustained observation of actual events. Also, storm surges occur within the temporal context of tidal variation, which must first be characterized through observation. Present standard approaches for measuring storm surges are not optimum. Thus, tidal gauges provide information at one point, whereas the heights reached by surges vary spatially. Also, post-surge ground surveys are expensive, laborious, and commonly lack comparison to similar data obtained for previous surges or for high tides. The advent of moderate spatial resolution, high temporal resolution remote sensing initiated by the launch of the two NASA MODIS sensors greatly reduces these constraints. For over a decade, daily coverage of most coastal land areas, though restricted by cloud cover, has systematically captured the maximum extents reached by both high tides and by storm surges. Automated water classification algorithms are now transforming the incoming image data into GIS water boundary files, again at daily or near-daily time steps. This paper provides a retrospective view of sample storm surges as mapped via these sensors and describes: (a) the present, MODIS-based surface water surveillance system, (b) the mapping enhancement to be provided by frequent-repeat, wide-swath satellite radar imaging, and (c) the emerging prospects for routine global surveillance of storm surge events. Such will be necessary if long-term trends are to be recognized, characterized, and understood, along coastal zones now being affected by both increasing subsidence and rising sea level.