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.

Conference Topics:

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.

Space-time statistics
Models for point processes
Lattice models
Geostatistics
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