The Nonlinear Markov Chain Geostatistics

摘要：

With the proposition of a Markov chain random field (MCRF) theory and its accompanying spatial measure - the transiogram, Markov chain has been extended into a nonlinear Markov chain-based geostatistical approach for one to muki-dimensional conditional (or unconditional) simulation, called Markov chain geostatistics (MCG). This new approach has nonlinear estimators, considers conditional independence of nearest known neighbors in cardinal directions, and can easily incorporate interclass relationships, which provide it advantages in dealing with categorical variables by generating more imitative patterns and less spatial uncertainty. This paper simply introduces the framework of MCG and recent technological development, and demonstrates some simulated results from MCG.

作者: Weidong Li Chuanrong Zhang

作者单位: Department of Geography, Kent State University, Kent, OH 44242, USA

会议类型: 国际会议

会议名称: The 12th Conference of the International Association for Mathematical Geology(第12届国际数学地质大会)

会议地点: 北京

会议语种:英文

页码: 573-578

在线出版日期: 2007-08-26（万方平台首次上网日期，不代表论文的发表时间）