地球科学进展 ›› 2004, Vol. 19 ›› Issue (2): 268 -274. doi: 10.11867/j.issn.1001-8166.2004.02.0268

综述与评述 上一篇    下一篇

地统计学方法进展研究
孙英君;王劲峰;柏延臣   
  1. 中国科学院地理科学与资源研究所,北京 100101;清华大学,北京 100084
  • 收稿日期:2003-06-30 修回日期:2003-11-15 出版日期:2004-12-20
  • 通讯作者: 孙英君(1976-),女,山东省聊城市人,博士生,主要从事GIS空间分析方面研究. E-mail:E-mail:sunyj@lreis.ac.cn
  • 基金资助:

    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:2002AA135230-1)资助

STUDY ON PROGRESS OF METHODS IN GEOSTATISTICS

SUN Yingjun 1 ,WANG Jinfeng 1 ,BAI Yanchen 2   

  1. 1.Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; 2. Tsinghua University, Beijing 100084, China
  • Received:2003-06-30 Revised:2003-11-15 Online:2004-12-20 Published:2004-04-01

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。

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.

中图分类号: 

[1] Andrew M Liebhold, et al. Geostatistics and geographic information systems in applied insect ecology[J]. Annual Review of Entomology, 1993, 38: 303-327.
[2] Bhatti A U, Mulla D, Frazier B. Estimation of soil properties and wheat yields on complex eroded hills using geostatistics and Thematic Mapper images[J]. Remote Sensing of Environment, 1991, 37: 181-191.
[3] Caers J. Geostatistics: From pattern recognition to pattern reproduction[A]. In: Nikravesh M, Aminzadeh F, Zadeh L,eds. Soft Computing and Intelligent Data Analysis in Oil Exploration[C].  Elsevier Publisher, 2001.1-22.
[4] Caers J, Zhang T. Multiple-point Geostatistics: A Quantitative Vehicle for Integrating Geologic Analogs into Multiple Reservoir Models[M]. Integration of Outcrop and Modern Analogs in Reservoir Modeling, AAPG Memoir, 2002.1-24.
[5] Caers J. History matching under training-image based geological model constraints[J]. SPE,2002, 77429: 1-16.
[6] Deutsch,Journel. GSLIBGeostatistical Software Library and User's Guide (2 nd)[M]. New York: Oxford University Press, 1998.
[7] Dungan J. Spatial prediction of vegetation quantities using ground and image data[J]. International Journal of Remote Sensing, 1998, 19: 267-285.
[8] Frykman P, Deutsch C V. Geostatistical scaling laws applied to core and log data[J]. SPE Paper Number 56822, Houston, TX, 1999: 887-898.
[9] Goovaerts P. Factorial Kriging analysis: A useful tool for exploring the structure of multivariate spatial soil information[J]. Journal of Soil Science, 1992, 43: 597-619.
[10] Goovaerts P. Study of spatial relationships between two sets of variables using multivariate geostatistics[J]. Geoderma, 1994, 62: 93-107.
[11] Goovaerts P. Geostatistical tools for characterizing the spatial variability of microbiological and physics-chemical soil properties[J]. Biology and Fertility of Soils, 1998, 27(4):315-334.
[12] Goovaerts P. Accounting for scale-dependent correlation in the spatial prediction of soil properties[A]. In: Gomez-Herenandez J, Soares A, Froidevaux R, eds. geoENVⅡ-Geostistics for Environmental Applications[C]. Dordrecht: Kluwer Academic Publishers,1999. 405-416.
[13] Goovaerts P. Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall[J]. Journal of Hydrology, 2000, 228:113-129.
[14] Goovaerts P. Geostatistical mapping of satellite data using pfield simulation with conditional probability fields[A]. In: Heuvelink G B M, Lemmens M J P M, eds. Proceeding of the 4th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences[C]. Amsterdam:2000. 253-260.
[15] Goovaerts P. Geostatistics for Natural Resources Evaluation[M]. New York: Oxford University Press,1997.
[16] Isaaks E H, Srivastava R M. Applied Geostatistics[M]. New York: Oxford University Press,1989.
[17] Journel A G. Fundamentals of geostatistics in five lessons. Volume 8 Short Course in Geology[C]. American Geophysical Union, 1989. 
[18]Journel A G. Conditioning geostatistical realization to non-linear volume averages[J]. Mathematical Geology, 1999, 31: 955-964.
[19]Journel A G.Combining knowledge from diverse information sources: An alternative to traditional data independence hypotheses[J]. Mathematical Geology, 2002, 34(5): 573-596.
[20] Journel, Huijbregts. Mining Geostatistics[M]. London: Academic Press,1978.
[21] Matheron B. The Theory of Regionalized Variables[M]. Fontainebleau:Centre de Morphologie Mathematique, 1971.
[22] Rao S, Journel A. Deriving conditional distributions from ordinary Kriging[A]. In: Baafi E Y, Schofield N A, eds. Geostatistics Wollongong'96 (Vol. 1)[C]. Dordrecht, The Netherlands, Kluwer:1997. 92-102.
[23] Strebelle S. Sequential Simulation Drawing Structure from Training Images[D]. Stanford University, 2000.
[24] Strebelle S. Conditional simulation of complex geological structures using multiplepoint statistics[J]. Mathematical Geology, 2002, 34: 1-22.
[25] Wakernagel H. Geostatistical techniques for interpreting multivariate spatial information[A]. In: Chung C F, Fabbri A G, Sinding-Larsen R, eds. Quantitative Analysis of Mineral and Energy Resources[C]. Redel, Dordrecht, 1998. 393-409.
[26] Bai Yanchen(柏延臣), Li Xin(李新). Spatial data analysis and spatial models[J]. Geographical Research(地理研究), 1999,18(2):185-190(in Chinese).
[27] Wang Jinfeng(王劲峰), Li Lianfa(李连发). A theoretic framework for spatial analysis[J]. Acta Geographica Sinica(地理学报), 2000,55(1):92-103(in Chinese).
[28]Wang Jinfeng(王劲峰), Bai Yanchen(柏延臣). Research and development of spatial analysis functions in GIS[J]. Journal of Image and Graphics(中国图象图形学报), 2001,6(A)(9): 849-853(in Chinese).
[29] Xiao Bin(肖斌), Zhao Pengda(赵鹏大), Hou Jingru(侯景儒). New development of geostatistics[J]. Advance in Earth Sciences(地球科学进展), 2000,3: 293-296(in Chinese).

[1] 方伟华,石先武. 面向灾害风险评估的热带气旋路径及强度随机模拟综述[J]. 地球科学进展, 2012, 27(8): 866-875.
[2] 殷水清,谢云,陈德亮,林小鹃,李维京. 日以下尺度降雨随机模拟研究进展[J]. 地球科学进展, 2009, 24(9): 981-989.
阅读次数
全文


摘要