Computating Changjiang's Spherical Center of Gravity and Analysis of Scaling Effects
Received date: 2009-08-28
Revised date: 2010-12-27
Online published: 2010-03-10
Changjiang River is a characteristic feature of China. The length of Changjiang River is about 6211.3 kilometers, the longest river in China, and the third longest river in the world. As a spatially distributed geographical feature, Changjiang not only has nonspatial attributes, such as length, but also many spatial attributes, for example, the center of gravity (or centroid), range, intensity, orientation, and shape in space. To study the spatial distribution of Changjiang River, this paper proposes a method for spatial statistics of spherical line features. To get rid of the effects of spherical curvature, a model of three dimension vector of spherical coordinates is used. To study the intrinsic scaling effects of spatial data, spatial partitioning of three different cell size(1 000 m,100 m and 10m) is proposed for the spatial statistics of Changjiang. To study the uncertainty of computational results, a simple spatial sampling method is applied. For simplicity, this paper takes the spherical center of gravity of Changjiang as an example. By ten times' 3% random sampling, the paper has also given the probability error of the center of gravity of Changjiang River. From the 10m spatial partitioning of Changjiang, the center of gravity of Changjiang results as N(30°25′37″),E(104°52′00″), based on which we get the spatial density 2D curve of Changjiang. The max spatial distribution percent every 100 kilometers away from the center of Changjiang is 22.2%, about 500~600 km. From 10 ten times spatial sampling, it can be concluded that, when 10 m spatial partitioning is applied, the error of spherical center is probably 50% less than 10 km, and 100% less than 17 km; when 100 m spatial partitioning is applied, the error of spherical center is probably 50% less than 20 km, and 100% less than 40 km; when 1 km spatial partitioning is applied, the error of spherical center is probably 50% less than 60 km, and 100% less than 100 km.Sphere-based spatial analysis is a global trend in GIS, this threedimensionalvector based spatial statistics method for spherical center of gravity also applicable to the areal features. Changjiang region is densely populated and so the study of Changjiang′s spatial distribution is very important. This paper can add up to people′s knowledge of Changjiang, which is also useful for the studies of economy, policy making related to the Changjiang, for the important geographical information or background information of Changjiang provided in this paper. The spatial data of Changjiang is from Data Center for Resources and Environmental Sciences of the Chinese Academy of Sciences (RESDC). Changjiang is extracted manually from the hydraulic network data.
SONG Tuan-Jiang , DIAO Zuo-Quan . Computating Changjiang's Spherical Center of Gravity and Analysis of Scaling Effects[J]. Advances in Earth Science, 2010 , 25(3) : 373 -283 . DOI: 10.11867/j.issn.1001-8166.2010.03.0373
[1] 人民网. 由6300到6211.3公里 这个数字能证明长江变短了？[EB/OL].http://www.people.com.cn/2002.2002.
[2] Chen Guojie, Approaches on natural calamities of the Yangtze River valley[J].Resources and Environment in the Yangtze Valley,1993, (1):50-58.[陈国阶, 长江流域自然灾害若干问题探讨[J].长江流域资源与环境, 1993,(1):50-58.]
[3] Changjiang Water Resources Commission, Water Administration and Water Resources Bureau. Changjiang Record[M].Beijing: Encyclopedia of China Publishing House, 2003.[长江水利委员会水政水资源局编.长江志[M].北京: 中国大百科全书出版社, 2003.]
[4] Zhao Zuoquan. From complex to simple: Attempting to measure the general system by use of the system geometry[J].Systems Engineering Theory and Practice,1997，17(8):131-134.[赵作权.从复杂到简单: 系统几何对一般系统度量的尝试[J].系统工程理论与实践, 1997，17(8):131-134.]
[5] Zhao Zuoquan. Global statistics of spatial distribution[J].A Literature Review，2009，28(1):1-8.[赵作权.地理空间分布整体统计研究进展[J].地理科学进展, 2009, 28(1):1-8.]
[6] Lefever D W. Measuring geographic concentration by means of the standard deviational ellipse[J].American Journal of Sociology,1926, 32: 89-94.
[7] Furfey P H. A note on Lefever's standard deviational ellipse[J].American Journal of Sociology,1927, 33: 94-98.
[8] Rogers A. A stochastic analysis of the spatial clustering of retail establishments[J].Journal of the American Statistical Association,1965,60: 1 094-1 103.
[9] Maceachren A M.Compactness of geographic shape: Comparison and evaluation of measures[J].Geografiska Annaler B,1985, 67: 53-67.
[10] King L J. The analysis of spatial forms and its relation to geographic theory[J].Annals of the Association of American Geographers,1969,59: 573-595.
[11] Glass L, Tobler W R. Uniform distribution of objects in a homogeneous field: Cities on aplain[J].Nature,1971,233: 67-68.
[12] Cliff A D, Ord J K. Model building and the analysis of spatial pattern in human geography[J]. Journal of the Royal Statistical Society B,1975,37: 297-348.
[13] Jones B G. Applications of centrographic techniques to the study of urban phenomena: Atlanta, Georgia 1940-1975[J].Economic Geography,1980, 56(3): 201-222.
[14] Kellerman A. Centrographic Measures in Geography\[M\].Concepts and Techniques in Modern Geography, 1981.
[15] Janelle D, Goodchild M. Diurnal patterns of social group distributions in a Canadian city[J]. Economic Geography,1983,59: 403-425.
[16] Gong J. Clarifying the standard deviational ellipse[J].Geographical Analysis,2002,34: 155-167.
[17] Getis A, Paelinck J. An analytical description of spatial patterns[J]. Espace Geographique,2004,1: 61-68.
[18] Kulldorff M. Tests of spatial randomness adjusted for an inhomogeneity: A general framework[J].Journal of the American Statistical Association,2006,101(475): 1 289-1 305.
[19] Barmore F E.Where are we? Comments on the concept of “Center of population”[J].The Wisconsin Geographer,1993, 9:8-21.
[20] Aboufadel, Edward, David A. A new method for computing the mean center of population of the United States[J].The Professional Geographer,2006,58:1, 65-69.
[21] Rossmo D K. Geographic Profiling[M].Boca Raton: CRC Press, 2000.
[22] Tober W. Global spatial analysis[J]. Computers, Environment, and Urban Systems,2002, 26: 493-500.
[23] Zheng Du，Chen Shupeng．Progress and disciplinary fronfiers of geographical research[J].Advances in Earth Science，2001，16(5)：599-606．[郑度，陈述彭．地理学研究进展与前沿领域[J]．地球科学进展，2001，16(5)：599-606．]
[24] WangJinfeng.Spatial Analysis[M].Beijing: Science Press, 2006.[王劲峰.空间分析[M]. 北京：科学出版社,2006.]
[25] Cressie N. Statistics for Spatial Data[M]. New York: Wiley,1993.
[26] David W S, Lee W J. Statistical Analysis of Geographic Information with ArcView GIS And ArcGIS[M]. John Wiley & Sons, Inc. , 2005.
[27] Neft D S. Statistical Analysis for Areal Distributions[M]. Philadelphia: Regional Science Research Institute,1966.
[28] Zhang Chao,Yang Binggen. Basic of Quantitative Geography(2nd edition)[M]. Beijing:Higher Education Press, 1991.[张超,杨秉赓.计量地理学基础（第二版）[M].北京：高等教育出版社, 1991.]
[29] Quattrochi D A, Goodchild M F. Scale in Remote Sensing and GIS[M].Boca Raton: CRC Press, 1997.
[30] Tate N J, Atkinson P M. Modelling Scale in Geographical Information Science[M].John Wiley and Sons, 2001.
[31] Griffith D A. Effective geographic sample size in the presence of spatial autocorrelation[J].Annals of the Association of American Geographers,2005,95(4):740-760.
[32] Fu Bojie, Lü Yihe. Scale and scale conversion method in ecology[J].Acta Ecologica Sinica, 2001, 21(12):2 096-2 105.[傅伯杰, 吕一河.生态学中的尺度及尺度转换方法[J].生态学报, 2001, 21(12):2 096-2 105.]
[33] Yue Tianxiang, Liu Jiyuan. Multi-scale problems in Eco-geographic modeling[J].Quaternary Research, 2003,23(3):256-261.[岳天祥, 刘纪远. 生态地理建模中的多尺度问题\[J\].第四纪研究, 2003, 23(3):256-261.]
[34] Zhu Xiaohua, Wang Jian, Chen Xia,et al. Study on the spatial fractal characteristic of coastline—A case study of Jiangsu Province，China[J].Geography Science,2001, 21(1):70-75.[朱晓华, 王建,陈霞,等.海岸线空间分形性质探讨——以江苏省为例[J]. 地理科学, 2001, 21(1):70-75.]
[35] William Bunge. Theoretical Geography[M].Lund: Royal University of Lund,1966.
[36] Jaap de Gruijter. Spatial sampling schemes for remote sensing[C]//Stein A, et al, eds. Spatial Statistics for Remote Sensing. Netherlands: Kluwer Academic Publishers,1999.
[37] Tongji University Mathematics Teaching and Research, Advanced Mathematics(4th edition, Voluem 1, 2)[M].Beijing: Higher Education Press, 2000.[同济大学数学教研室编.高等数学（第四版）（上、下册）[M].北京:高等教育出版社, 2000.]
[38] Xu Yang, Yang Xingyun. Spatial Analytical Geometry and Applications\[M\].Harbin: Harbin Institute of Technology Press，2006.[徐阳,杨兴云编著.空间解析几何及其应用(高等学校十一五规划教材)[M].哈尔滨:哈尔滨工业大学出版社，2006.]
[39] US Census Bureau. Centers of Population Computation for 1950, 1960, 1970, 1980, 1990 and 2000[M].Washington DC,2001.
[40] Gentle J E. Random Number Generation and Monte Carlo Methods[M].New York: Springer,2003.
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