_{by Gerard B.M. Heuvelink (Wageningen University, The Netherlands) and James D. Brown (National Oceanic and Atmospheric Administration, USA)}

Summary: The Spatial Uncertainty Propagation is a two-day workshop that presents theory and practice of spatial uncertainty propagation analysis, by presenting and discussing various uncertainty propagation techniques. The emphasis is on Monte Carlo simulation methods. Workshop participants learn to use the Data Uncertainty Engine software tool, which is specifically designed to help users define, assess, store and simulate uncertain spatio-temporal environmental data. Considerable attention is given to the effect of cross- and spatio-temporal correlations on the results of an uncertainty analysis and on methods to determine the relative contribution of individual uncertain inputs to the accuracy of the final result.

Venue: Monday 23 and Tuesday 24 June, 2008; Pine City Hotel Shanghai, China

Participants: shibiaobai21()163.com; mario.caetano()igeo.pt; hugo.carrao()igeo.pt; shaofei.chen()utd.edu; Yun.Chen()csiro.au; gannd()fiu.edu; garrigue()pop600.gsfc.nasa.gov; azalea_gu()163.com; lzu8848d13()yahoo.com.cn; hengl()science.uva.nl; huangcl()lzb.ac.cn; robrien()csu.edu.au; p.posen()uea.ac.uk; ranyh()lzb.ac.cn; psarmento()igeo.pt; wlhtj2001()yahoo.com.cn; wujuebo()gmail.com; jkyamamo()usp.br; eunhye()buffalo.edu; nonolin16()hotmail.com; baihx()lreis.ac.cn

Overheads:

• #1 Intro;
• #2 Methods;
• #3 DUE;
• #4 Examples;
• #5 Other

Practicals: instructions; datasets: [Geul]; [Baranja Hill];

Software:

• R including the packages (sp, rgdal, gstat, foreign, lattice);
• DUE requires the JAVA Runtime Environment
  • DUE v3.1 (binaries; unzip);
  • Source code (unzip);
  • User's manual

References:

1. Brown, J.D. and Heuvelink, G.B.M. 2007. The Data Uncertainty Engine (DUE): A software tool for assessing and simulating uncertain environmental variables. Computers & Geosciences, 33(2): 172-190.
2. Heuvelink, G.B.M. 2002. Analysing uncertainty propagation in GIS: why is it not that simple?. In: G.M. Foody and P.M. Atkinson, Editors, Uncertainty in Remote Sensing and GIS, Wiley, Chichester (2002), pp. 155 –165.
3. Heuvelink, G.B.M., Brown, J.D., Van Loon, E.E., 2006. A Probabilistic framework for representing and simulating uncertain environmental variables. International Journal of Geographic Information Science, 21(5): 497-513.