Spatial Statistics 2017: One World: One Health
4-7 July 2017 | Lancaster University, 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 registration and abstract submission systems are now closed.
Please note that a workshop will be held on 4 July and the conference will start on 5 July.
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.
- Models for point processes
- Lattice models
- Copulas in space and time
- Spatial extremes
- Change-point analysis
- Estimation methods
- Issues of scale: upscaling and downscaling methodology
- Stochastic geometry, random sets and stereology
- Causal statistical modeling
- Image analysis (e.g. satellite sensor image time-series, DNA data, brain imaging)
- Predictive modelling
- Spatial data quality and uncertainty
- New spatial data sources (e.g. social media, Google, citizen science, crowd sourced data)
- Large dimensional big spatial data
With these methods being applied in a range of relevant domains. For the theme of the conference, we particularly invite contributions in:
- Statistical aspects of epidemiology
- Geo-Health and One Health
- Plant and animal diseases
- Health and Global change
- Zoonotic and vector-borne diseases (e.g. emerging epidemics)
- Hazards, disasters and risks (e.g. outbreaks, risk mapping)
- Ecology (e.g. dispersion, migration, colonisation and invasion of species)
- Spatial econometrics