报告人：Gerard B.M. Heuvelink,  

Soil Geography and Landscape Group, 

Wageningen University, The Netherlands  

内容简介：Spatial uncertainty propagation analysis is usually concerned with analysis of how uncertainties in the inputs to spatial environmental models propagate to the model output. However, input uncertainty is only one of several sources of uncertainty that affect the accuracy of the model output. Often there are also uncertainties about the parameters and structure of the model. In many cases model uncertainty may even be the dominant source of uncertainty, which implies that it cannot be ignored if a realistic assessment of the overall output uncertainty is to be made. In this work we present an uncertainty analysis framework that integrates all sources of uncertainty. The framework assumes that the uncertainties about the model inputs have been derived externally, while uncertainties about model parameters and model structure are obtained using Bayesian calibration. In a first stage, model structural uncertainty is represented by an additive stochastic residual. Prior distributions for the parameter and structural uncertainty are defined, and next observations of the model output are used to calculate posterior distributions. The Bayesian calibration procedure takes into account that part of the discrepancies between observed and predicted model output is caused by input uncertainty and by observational error. Once the calibration is completed and all error sources have been characterized by probability distributions, the uncertainty propagation analysis is done using a straightforward Monte Carlo approach. The framework is illustrated with a simple example in which a multiple regression model is used to predict the moisture content at wilting point from soil porosity and moisture content at field capacity for a study area in the floodplain of the Allier river, France. 

报告人简介：Gerard Heuvelink博士目前是世界土壤信息中心（ISRIC World Soil Information）计量土壤学与数字土壤制图领域的高级研究员，同时也是荷兰Wageningen大学土壤地理和景观研究组的副教授和中国科学院地理科学与资源研究所的客座教授。他从博士期间开始从事空间数据不确定性及误差传递模型研究，经过多年工作现已发表250余篇关于地统计、空间不确定性分析和计量土壤学的相关论文和著作。论文具有较高引用率，其中多篇论文被评为期刊年度最佳论文。Gerard Heuvelink博士曾在六个欧洲研究项目（如，UNCERSDSS, HarmoniRiB, Intamap, UncertWeb）中担任过主席或成员，同时还是 European Journal of Soil Science 和 Spatial Statistics 的副主编，Geoderma, Environmental and Ecological Statistics, International Journal of Applied Earth Observation and Geoinformation 和 Geographical Analysis等杂志的编委，并在多个与GIS和spatial accuracy相关的国际会议中出任指导委员会成员。 

主 持 人：葛咏 研究员 

报告时间：2014年5月23日（星期五）上午9:00  

报告地点：中科院地理资源所2209会议室 

主办单位：资源与环境信息系统国家重点实验室