During humanitarian emergencies, well-timed information on affected populations is central in planning humanitarian responses and the optimum allocation of available resources. However, this is usually only available following an on-ground assessment which, in most of the cases, comes too late to contribute to the initial decision-making process that informs the first wave of humanitarian response. To address this problem, a spatial model was developed for the assessment of the flood-affected population in a near real-time scenario. A flood extent vector, extracted from MODerate resolution Imaging Spectro-radiometer daily images, was superimposed on a LandScan population grid to estimate the population count living in the flooded area, aggregated by their respective administrative level. The methodology was found to be both time-and cost-efficient for riverine floods. The model was tested for its accuracy using an on-ground initial vulnerability assessment and the figures matched to within 80-90%. This model can be used with a confidence level of +/- 10% for riverine floods.