Speaker : Alexandre Wadoux, PhD Researcher, Wageningen University, The Netherlands Title of Talk: Sampling Design Optimization for Spatial Processes Date: 21 March, 2017 (Tuesday) Time: 04:00 p.m. - 05:00 p.m. Venue: First Floor Seminar hall, CE. ______________________________________________________________________________________ Speaker Bio: ************ Alexandre Wadoux is a PhD candidate at Wageningen University. He completed an M.Sc. in Physical Geography at the University of Tübingen (Germany) where he conducted research on soil spectroscopy and spatial monitoring. His current work focuses on statistical analysis of environmental variables and sampling design optimization for uncertainty analysis. He is part, since 2015, of the EU funded FP7 Marie Curie Initial Training Network (ITN) ‘Quantifying Uncertainty in Integrated Catchment Studies (QUICS)’. Brief abstract: ************** Environmental models need input data and data for calibration and validation. For the input of distributed hydrological models as well as for spatial analysis, we need to interpolate a target variable from a finite number of spatial observations (e.g. rainfall, temperature, soil variable). As a consequence, the accuracy of the interpolated maps will depend partly on the sampling location of the observations. The aim of this presentation is to present how to optimize sampling patterns to gain maximum information for a given budget and how to find the optimal sampling design for minimization of a given criterion. The presentation is structured in three chapters. In the first chapter we review some knowledge on space and space-time interpolation to produce maps, which can later be used as input for environmental models. In the second chapter we show how we can re-organize a sampling design in order to find an optimal sampling pattern for our model. The last chapter is a computer example. Ten sampling locations are added manually to a case study for prediction of a soil pollution variable. We demonstrate that sampling theory can help to obtain the best locations.