In the style of a three-word-Monday this article outlines my current research and the general bigger issue of natural hazard exposure assessment and population mapping. Population exposure to flooding in the UK, Spain and Pakistan are recent notable examples from the media this week.
The term ‘model’ might often evoke an irrational fear or sudden bout of cyberphobia to some readers of academic literature. However, this need not be the case. If a new viewing certification system were to be devised, I would rate this “FJF, Fairly Jargon Free: but may contain some conceptual language”.
Accurately estimating the spatio-temporal characteristics (movements in time and space) of a population is a key component in natural hazard risk assessment. Often this has been limited by the availability of data, software and tools. By design, most GIS inherently deal with space and have limited capacity to handle truly temporal information. Historically, space is often represented ‘over time’ rather than ‘in time’ such as the traditional geography time-slice. The development of Surfacebuilder247 provides a new software tool to model population densities as a raster grid in time. There are many transient populations, such as people travelling for work, school and leisure at different times of the day, who are not accounted for in traditional population datasets.
An example might be a Saturday population peak in a busy city centre full of shoppers or a surge of spectators at a large event or sports fixture. During the P&O 175th anniversary celebrations, all seven cruise ships departed Southampton together with a combined passenger and crew total of 40,000 people, a considerable fluctuation to the city’s population.
The added advantage of using gridded population estimations removes arbitrary administrative boundaries that delineate many population datasets, but have no bearing on the footprint of natural hazards. There is an even greater need to improve population estimations regarding assessing natural hazard exposure and to promote reliable and informed decisions for emergency planning and preparedness.
Further information: Research website