Rapid assessment of a flood‐affected population through a spatial data model

Abstract

AbstractDuring 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.