| 地统计学方法进展研究 |
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| 引用本文： | 孙英君,王劲峰,柏延臣.地统计学方法进展研究[J].地球科学进展,2004,19(2):268-274. |
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| 作者姓名： | 孙英君 王劲峰 柏延臣 |
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| 作者单位： | 1. 中国科学院地理科学与资源研究所,北京,100101
2. 清华大学,北京,100084 |
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| 基金项目： | 国家高技术研究发展计划 ( 863计划 )项目“空间信息分析及原型研发”(编号 :2 0 0 2AA13 5 2 3 0 1)资助 |
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| 摘 要： | 地统计学近年来成为空间分析的重要工具，其应用领域广泛分布在自然科学的众多领域。系统地论述了地统计学理论方法的进展，给出地统计学的总体理论框架，它包括局部估值、不确定性预测、随机模拟及多点地统计学四部分。并指出所有这些方法的理论基础是随机变量理论，其核心是利用变异函数获得研究对象的空间分布规律。同时，分别介绍了每个部分的具体方法，特别提到了新发展的多点地统计学方法。最后对地统计学的软件应用加以总结，指出将GIS与地统计学相结合是一种必然的趋势。
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| 关 键 词： | 地统计学 克里格方法 随机模拟 多点地统计学 |
| 文章编号： | 1001-8166(2004)02-0268-07 |
| 修稿时间： | 2003年6月30日 |
STUDY ON PROGRESS OF METHODS IN GEOSTATISTICS |
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| SUN Ying jun ,WANG Jin feng ,BAI Yan chen.STUDY ON PROGRESS OF METHODS IN GEOSTATISTICS[J].Advance in Earth Sciences,2004,19(2):268-274. |
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| Authors: | SUN Ying jun WANG Jin feng BAI Yan chen |
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| Institution: | 1.Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; 2. Tsinghua University, Beijing 100084, China |
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| Abstract: | Geostatistcs has been an important tool for spatial analysis recently, it has been applied many fields of natural science, such as geography, ecology, soil science and so on. The paper discusses the progress in the theory method of Geostatistics. The whole framework has been pointed out, including estimation, local uncertainty, stochastic simulation and multi point simulation. Especially the new methods, for example Sequential Gaussian Simulation, LU Simulation, P field simulation, Annealing Simulation are described. The paper analyzes the difference between multi point simulation with the traditional geostatistics methods. That is the breakthrough of two point method variogram to training image to describe the spatial structure of objects. Meanwhile, the paper makes a comment on the software of Geostatistics. The need of graphic user's interface, high quality image input and output, together with the absence of spatial analysis function, caused the combination of Geostatistics and GIS is an inevitable trend. |
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| Keywords: | Geostatistics Kriging method Stochastic Simulation Multi point Simulation |
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