geography and environment 24/7 population modelling for natural hazard assessment alan smith...
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Geography and Environment
24/7 Population modelling for natural hazard assessment
Alan SmithUniversity of Southampton, UKColloquium on Spatial Analysis, Copenhagen, 10 January 2013
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Acknowledgments
Developing the “Pop 24/7” methodologies:
• Professor David Martin
• Samantha Cockings
Part of a PhD funded by the Economic and Social Research Council
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Background• Better population estimations are required for
hazard risk assessment
• Censuses typically provide a decadal ‘night-time’ population estimation
• This does not take into account the large fluxes of temporary populations during the day
• Events of 2011/12 have focused global attention on natural hazards and their impacts
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Christchurch, NZ
5Miyako, NE Japan
6Southampton, New York, USA…
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…Southampton, UK
Conventional density maps
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“Pop 24/7” overview• Spatio-temporal gridded population modelling
– Variable kernel density estimation (KDE)– Utilises population centroids– Redistributes resident populations according to
a temporal profile– Population subgroups
• Removal of arbitrary administrative boundaries
• Allows locations of zero population density (Eg. Water)
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Methods• Distribution between population centroids
• Creation of temporal profile using ancillary data sources
• Building new datasets to model (Eg. Retail)
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Data inputs
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Large user and small business count UPCsUsing commercial postcodes as georeferenced points to receive a known or estimated transient ‘daytime’ population (E.g. Shop locations for shoppers)
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Temporal ProfileA retail example of a temporal profile derived from the Time Use Survey 2000 indicating potential shopper numbers for a given time.
11:59:59 PM 03:19:59 AM 06:40:00 AM 10:00:00 AM 01:20:00 PM 04:40:00 PM 08:00:00 PM 11:20:00 PM0.00
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Mon-Fri
Saturday
Sunday
Time
P(R
esp
ondents
Shoppin
g)
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Results• Variable grid size, currently using 250 metre
resolution
• Visualization for public communication
• Population weighted to background mask
• Combination and analysis with hazard footprint data
• Application to a UK flooding scenario, using the Environment Agency’s ‘Flood Map’.
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Example weekday population
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Example weekday population
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Example weekday population
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Example weekday population
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Example weekday population
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Example weekday population
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Example weekday population
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Example weekday population
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Combing spatio-temporal population information and hazard footprints for analysis in GIS
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Flood Map data
Fluvial risk:1% (1:100 years)
Coastal risk:0.5% (1:200 years)
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Next steps• Further analysis of results
• Continued development of datasets and temporal profiles
• Application to a hazard scenario
• Demonstrate improved exposure estimations
• Advances in natural hazard risk management
• Many more potential applications…
