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January 8, 2015
Call for Papers for Spatial Statistics Conference

Abstract submissions are invited on the conference topics below and should be submitted using the online submission system by the 13 February 2015.

Conference Chairs:

Denis Allard, Avignon, France
Alfred Stein, Twente University, The Netherlands

The next Spatial Statistics conference will be held in Avignon, France, from the 9-12 June 2015 under the theme, Emerging Patterns. Spatial statistics is a rapidly developing field involving the quantitative analysis of spatial data and the statistical modelling of spatial variability and uncertainty. Spatial statistics is of critical importance to the use and interpretation of VGI, webservices, remotely sensed data and further processing within a GIS environment. Applications of spatial statistics are for a broad range of environmental disciplines (agriculture, geology, soil science, hydrology, ecology, oceanography, forestry, meteorology and climatology) as well as for socio-economic disciplines (human geography, spatial econometrics, epidemiology and spatial planning). The availability of GIS systems and affordable geospatial databases has fuelled the interest in the statistical analysis of geographic data. The theme, Emerging Patterns in Spatial Statistics will highlight trends on various topics such as ‘new sources of spatial data’, ‘predictive modelling’, ‘disease mapping’, ‘hazards, disasters and risks’, ‘climate change’ and ‘tipping points’.

It 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 you keep abreast of recent developments in this fast evolving field.

Conference Topics

  • Space-time statistics (e.g. point patterns models, estimation methods, large dimensions, scale issues)
  • Spatial data quality and uncertainty
  • Parameter estimation in PDEs
  • Stochastic geometry, tesselation, point processes, random sets
  • Spatial econometrics
  • New spatial data sources (e.g. big, data, social media, Google, citizen science, crowd source maps)
  • Image analyses (e.g. satellite images time series, DNA data, nano particles, nervous systems)
  • Predictive modelling
  • Tipping points (e.g. sea-level rise, socio-economic shifts)
  • Hazards, disasters and risks (e.g. tsunamis, earthquakes, landslides, air pollution levels)
  • Global change (e.g. stochastic weather generators)
  • Health, medical and epidemiology
  • Plant and animal epidemiology (emerging epidemics)
  • Ecology (e.g. dispersion, migration, colonisation and invasion of species)

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