Spatial Statistics 2017: One World: One Health
4-7 July 2017 | University of Lancaster, Lancaster, UK
Welcome to Spatial Statistics, which will be held in Lancaster, UK, from the 4-7 July 2017 under the theme, One World: One Health.
The availability of GIS systems, remote sensing platforms and affordable geospatial databases has fueled interest in the statistical analysis of geographic data. Spatial statistics is a rapidly developing field involving the quantitative analysis of such spatial data and spatio-temporal data, and the statistical modelling of related variability and uncertainty.
The theme, One World: One Health in Spatial Statistics will highlight trends in various topics such as ‘disease mapping’, ‘disease systems modelling, ‘new sources of spatial data, including movements and trajectories’, ‘hazards, exposure and risk’, ‘geo-health’ and, of course, ‘one health’.
At the same time, the conference will also offer opportunities to address developments in environmental disciplines such as agriculture, geology, soil science, hydrology, ecology, oceanography, forestry, meteorology and climatology, as well as in socio-economic disciplines such as human geography, spatial econometrics and spatial planning.
During the conference, special attention will be given to the contributions of
Prof. Peter Diggle, who is a world-leading proponent of spatial statistics, with the University of Lancaster as his home base.
This is a significant opportunity for you to hear from leading scientists in the field and to network with colleagues in industry and academia to ensure that you keep abreast of recent developments in this exciting field of science.
Abstract Submission Deadline: 13 January 2017
Oral and poster abstracts are now invited on the following topics and should be submitted using the online abstract submission system.
- Health, medicine and epidemiology
- Zoonotic and vector-borne diseases (e.g. emerging epidemics)
- Geo-Health and One Health
- Plant and animal diseases
- New spatial data sources (e.g. big, data, social media, Google, citizen science, crowd source maps)
- Space-time statistics (e.g. point patterns models, estimation methods, large dimensions, scale issues)
- Causal statistical modeling
- Global change (e.g. stochastic weather generators)
- Spatial data quality and uncertainty
- Stochastic geometry, tesselation, point processes, random sets
- Image analyses (e.g. satellite sensor image time-series, DNA data, brain imaging)
- Predictive modelling
- Hazards, disasters and risks (e.g. outbreaks, risk mapping)
- Ecology (e.g. dispersion, migration, colonisation and invasion of species)
- Spatial econometrics
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- Professor Peter M. Atkinson, Lancaster University, UK
- Professor Alfred Stein, University of Twente, The Netherlands