华北平原土壤重金属元素空间自相关研究
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摘要
现今土壤中化学元素的组成、分布与分配规律，是第四纪地质历史演化的结果，受土壤表生地球化学作用的控制，因此不同的元素在空间上的分布存在着一定的模式。总体上来说，每一种空间模式，只是反映了空间元素在某一时间阶段的空间过程，随着时间的推移，空间元素在空间过程的作用下，其空间模式也会发生变化，如果空间过程比较稳定，且作用范围大，那么空间元素的空间分布模式在一定时间阶段内是比较稳定不变的，反之则是快速变化的。因此概化和定量刻画空间模式必须要清楚影响空间现象分布的复杂的空间过程，要对空间过程进行模拟，不管是统计模拟还是公式化定量模拟，都需要对空间信息的空间模式加以详细研究。
本文利用华北平原现今最为完整的大量土壤调查数据，对华北平原As、Cd、Cr、Cu、Hg、Ni、Pb和Hg等8种重金属元素含量进行了统计分析和对比研究，对每种元素含量在华北平原的分布特点进行了综合分析与描述，并对八种重金属元素进行了单因子污染评价和综合污染评价，完整呈现了华北平原土壤重金属现状特点。
为了更为深入地了解每种重金属元素在空间上的分布模式，本文将空间自相关分析技术引入到土壤元素空间分布模式研究上。本文首先对空间自相关和空间模式进行了理论研究，设计了不同网格模式进行了理论分析，展示了空间自相关技术对空间模式刻画的原理与能力，同时还从理论上深入研究了不同空间分辨率下的空间模式和对空间自相关的关系，并首次定量建立了理论关系，从而为具体研究华北平原8种重金属元素的空间模式提供了理论支撑。本文利用空间自相关技术对华北平原8种重金属的空间自相关模式进行了分析研究，建立了每种元素与空间分辨率的定量关系，最后得出了调查和监测两个尺度下每种重金属元素的合适网格密度与样本容量，该项成果和方法为下一步在华北平原开展土壤重金属调查和监测工作提供了重要的参考。
In present, soils elements constituent、distribution of elements and distribute ruleof elements is the result which Quaternary Period geology evolvement process.Different soil elements come into being different spatial pattern because of controllingfor soil geochemical process in earth surface. In general, each pattern is the reflectionof the underlying spatial process at a specific stage of time and it also influences theprocess for the next stage. Spatial pattern will be steady at a specific stage of timeif spatial process is be steady and spatial effect range is wide. Accordingly, thecapability of generalizing and quantifying spatial patterns is a prerequisite tounderstanding the complicated processes governing the distribution of spatialphenomena.
In the paper, The heavy metal elements (As、Cd、Cr、Cu、Hg、Ni、Pb、Hg) is beanalyzed use mathematics statiscs method. The soils data of used is very integrate sofar in north china plain. The characteristic of soil heavy metal spatial distributing is bedescribed and analyzed. Soil heavy metal contaminations evaluate on single factorand integrated.
For comprehending soil heavy metal spatial patterns penetrability, spatialautocorrelation method is introducted in this paper. Firstly, spatial autocorrelation andspatial patterns is researched in theory. The characteristic and capability of spatialautocorrelation technique on portraying spatial patterns is exhibited by studingdifferent spatial grid pattern which is designed by the paper author. Simultaneity, thelog-lines ralation between spatial pattern and spatial autocorrelation at differentspatial resolution is studied which provide a theory foundation at studing soil heavymetal spatial patterns in North China plain. In this paper, soil heavy metal spatialpatterns in North China plain are studied detailedly basing on spatial autocorrelationtechnique. The network density is counted by spatial autocorrelation technique whichafford important reference in soil investigate and soil monitoring.
本文利用华北平原现今最为完整的大量土壤调查数据，对华北平原As、Cd、Cr、Cu、Hg、Ni、Pb和Hg等8种重金属元素含量进行了统计分析和对比研究，对每种元素含量在华北平原的分布特点进行了综合分析与描述，并对八种重金属元素进行了单因子污染评价和综合污染评价，完整呈现了华北平原土壤重金属现状特点。
为了更为深入地了解每种重金属元素在空间上的分布模式，本文将空间自相关分析技术引入到土壤元素空间分布模式研究上。本文首先对空间自相关和空间模式进行了理论研究，设计了不同网格模式进行了理论分析，展示了空间自相关技术对空间模式刻画的原理与能力，同时还从理论上深入研究了不同空间分辨率下的空间模式和对空间自相关的关系，并首次定量建立了理论关系，从而为具体研究华北平原8种重金属元素的空间模式提供了理论支撑。本文利用空间自相关技术对华北平原8种重金属的空间自相关模式进行了分析研究，建立了每种元素与空间分辨率的定量关系，最后得出了调查和监测两个尺度下每种重金属元素的合适网格密度与样本容量，该项成果和方法为下一步在华北平原开展土壤重金属调查和监测工作提供了重要的参考。
In present, soils elements constituent、distribution of elements and distribute ruleof elements is the result which Quaternary Period geology evolvement process.Different soil elements come into being different spatial pattern because of controllingfor soil geochemical process in earth surface. In general, each pattern is the reflectionof the underlying spatial process at a specific stage of time and it also influences theprocess for the next stage. Spatial pattern will be steady at a specific stage of timeif spatial process is be steady and spatial effect range is wide. Accordingly, thecapability of generalizing and quantifying spatial patterns is a prerequisite tounderstanding the complicated processes governing the distribution of spatialphenomena.
In the paper, The heavy metal elements (As、Cd、Cr、Cu、Hg、Ni、Pb、Hg) is beanalyzed use mathematics statiscs method. The soils data of used is very integrate sofar in north china plain. The characteristic of soil heavy metal spatial distributing is bedescribed and analyzed. Soil heavy metal contaminations evaluate on single factorand integrated.
For comprehending soil heavy metal spatial patterns penetrability, spatialautocorrelation method is introducted in this paper. Firstly, spatial autocorrelation andspatial patterns is researched in theory. The characteristic and capability of spatialautocorrelation technique on portraying spatial patterns is exhibited by studingdifferent spatial grid pattern which is designed by the paper author. Simultaneity, thelog-lines ralation between spatial pattern and spatial autocorrelation at differentspatial resolution is studied which provide a theory foundation at studing soil heavymetal spatial patterns in North China plain. In this paper, soil heavy metal spatialpatterns in North China plain are studied detailedly basing on spatial autocorrelationtechnique. The network density is counted by spatial autocorrelation technique whichafford important reference in soil investigate and soil monitoring.
引文
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23. Isaaks,Edward H. Srivastava,R.M. Applied geostatistics. Oxford Univ. Pr.,Inc.1989
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38. Upton, G.&Fingleton, B.(1985) Spatial Data Analysis by Example,John Wiley&Son
39. W. N. Venables and B. D. Ripley. Modern Applied Statistics with S (4th edition).Springer,2002
40. Wulder, M., Boots, B.(1998) Local spatial autocorrelation characteristics ofremotely sensed imagery assessed with Getis statistic, International Journal ofRemote Sensing,19(11):2223-2231
41. Xiao-Ni Huo, Wei-Wei Zhang, Dan-Feng Sun. Spatial Pattern Analysis of HeavyMetals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics.Int. J. Environ. Res. Public Health,2011,8,2074-2089
42. Yue Hone Chou. Map Resolution and Spatial Autocorrelation. GeographicalAnalysis,1991,23(3):228~111
43.梁艳平,钟耳顺,朱建军.城市人口分布的空间相关性分析.工程勘察,2003,4:48-50
44.孟斌,王劲峰,张文忠，等.基于空间分析方法的中国区域差异研究.地理科学,2005,25(4):393-400
45.刘旭华,王劲峰.空间权重矩阵的生成方法分析与实验.地球信息科学,2002,2:38-44
46.李天生，周国法.空间自相关和分布型指数研究.生态学报,1994,14(3):327-331
47.刘永生，李瑞敏.不同方法下土壤重金属元素空间最大变异距离研究——以浙江上虞为例.岩矿测试,2007,26(4).
48.胡克林，张凤荣，吕贻忠，等．北京市大兴区土壤重金属含量的空间分布特征[J]．环境科学学报，2004，24(3)：463－468．
49.郑袁明，陈同斌，陈煌，等．北京市近郊区土壤镍的空间结构及分布特征[J]．地理学报，2003，58(3)：470－476．
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2. Akima, H.(1996). Algorithm761: scattered-data surface fitting that has theaccuracy of a cubic polynomial. ACM Transactions on Mathematical Software,22,362-371.
3. Andrienko N and Andrienko G.(2006)Exploratory Analysis of Spatial andTemporal Data.2006，Springer，Berlin.
4. Anselin, Luc. Local Indicators of Spatial Association—LISA. GeographicalAnalysis,1995,27(2):93-115
5. Anselin, Luc. and A. Getis. Spatial statistical analysis and GeographicInformation Systems. Annals of Regional Science,1992,26:19-33
6. Anselin L. The Future of Spatial Analysis in the Social Sciences[J]. GeographicInformation Sciences,1999,5(2):67-76.
7. Bao, Shuming and Mark S. Henry. Heterogeneity issues in local measurements ofspatial association.Geographical Systems,1996,3:1-13
8. Boots, B. Local measures of spatial association. Ecoscience2002,9,168-176.
9. Cambardella C A,Oorman A T, Novak J M, et al. Field-scale variability of soilproperties in centralIowa soils. Soil Sci Soc Am J,1994,58:1501-1511.
10. Chou, Y.-H.(1995) Spatial pattern and spatial autocorrelation.Spatial informationtheory: a theoretical basis for GIS (ed. byA.U. Frank and W. Kuhn), pp.365–376.Springer-Verlag,Berlin.
11. Cliff, A.&Ord, J. K. Spatial Autocorrelation. London: Pion,1973
12. Cliff, A.&Ord, J. K. Spatial Processes: Models and Applications. London:Pion,1981
13. Cressie N A C. Statistics for Spatial Data. Wiley Series In Probability andMathematical Statistics. Rev ed. New York: Wiley&Sons,1993.
14. Dale, M.R.; Fortin, M.J. Spatial autocorrelation and statistical tests in ecology.Ecoscience2002,9,162-167.
15. Forsythe, G. E., Malcolm, M. A. and Moler, C. B.(1977) Computer Methods forMathematical Computations.
16. Getis, Arthur and Ord, J. Keith. The Use of a Local statistic to Study theDiffusion of AIDS from San Franciso, Paper presented at the42nd NorthAmerican Meetings of the Regional Science Association International inCincinnati, November,1995.
17. Getis, A., Ord, J. K. The Analysis of Spatial Association by Use of DistanceStatistics. Geographical Analysis,1992,24(3):189-206
18. Goovaerts P. Geostatistics in soil science: state-of-the-art and perspectives.Geoderm,1999,89:1-45
19. Goodchild, M. F. Spatial Autocorrelation. CATMOG47, Geobooks: NorwichUK.1986,pp.6-25.
20. Goodchild, M. F., Haining, R. P. and Wise, S. Integrating GIS and spatial dataanalysis: problems and possibilities. In International Journal of GeographicalInformation Systems.1992,6(5):407-423
21. Haining, R. P. Spatial Data Analysis in the Social and Environmental Science.Cambridge University Press.1990
22. Hu, K.L.; Zhang, F.R.; Li, H.; Huang, F.; Li, B.G. Spatial patterns of soil heavymetals in urban-rural transition zone of Beijing. Pedosphere2006,16,690-698.
23. Isaaks,Edward H. Srivastava,R.M. Applied geostatistics. Oxford Univ. Pr.,Inc.1989
24. Kim Lowell.,1996. Positive Spatial Autocorrelation as a Necessary But NotSufficient Condition for Reliable Spatial Interpolation. In: Proceedings of theSpatial Information Research Centre's8th Colloquium. University of Otago, NewZealand, pp.43–48.
25. MathSoft. S+SpatialStats User’s Manual for Window and Unix, Data AnalysisProducts Division, MathSoft, Inc., Seattle, WA.1996
26. Moran,P.A.P. Notes on continuous stochastic phenomena.1950,Biometrika,37:17
27. Ord,J.K. and Getis,A. Local spatial autocorrelation statistics:Distributional issuesand application. Geographical Analysis,1995,27(4):286~306
28. Odland, J. Spatial Autocorrelation. Sage: Beverly, CA.1987
29. Overmars, K.P.; de Koning, G.H.J.; Veldkamp, A. Spatial autocorrelation inmulti-scale land use models. Ecol. Model.2003,164,257-270.
30. Pebesma, E.J. and Wesseling, C.G. Gstat, a program for geostatistical modelling,prediction and simulation. Computers&Geosciences,1998,24(1), pp.17–31
31. Paelinck, Jean H. P. and Klaassen, Leo H. Spatial Econometric. Saxon House,England.1979
32. Rey S, Montouri B. US regional income convergence: a spatial econometricperspective[J]. Regional Studies,1999,33:143-1564.
33. Ripley, B.D. Spatial Statistics in R. R News,2001.Vol1/2,14–15.
34. Ripley, B.D. Spatial Statistics. Cambridge: Cambridge University Press,1981.
35. Schabenberger O and Gotway CA. Statistieal Methods for Spatial DataAnalysis.CHAPMAN&HALL/CRC，2005，Newyork.
36. Sokal, R.R. and Oden, N.L.1978a. Spatial autocorrelation in biology1.Methodology. Biological Journal of the Linnean Society,10:199
37. Sokal, R.R. and Oden, N.L.1978b. Spatial autocorrelation in biology2. Somebiological implications and four applications of evolutionary and ecologicalinterest. Biological Journal of the Linnean Society,10:229
38. Upton, G.&Fingleton, B.(1985) Spatial Data Analysis by Example,John Wiley&Son
39. W. N. Venables and B. D. Ripley. Modern Applied Statistics with S (4th edition).Springer,2002
40. Wulder, M., Boots, B.(1998) Local spatial autocorrelation characteristics ofremotely sensed imagery assessed with Getis statistic, International Journal ofRemote Sensing,19(11):2223-2231
41. Xiao-Ni Huo, Wei-Wei Zhang, Dan-Feng Sun. Spatial Pattern Analysis of HeavyMetals in Beijing Agricultural Soils Based on Spatial Autocorrelation Statistics.Int. J. Environ. Res. Public Health,2011,8,2074-2089
42. Yue Hone Chou. Map Resolution and Spatial Autocorrelation. GeographicalAnalysis,1991,23(3):228~111
43.梁艳平,钟耳顺,朱建军.城市人口分布的空间相关性分析.工程勘察,2003,4:48-50
44.孟斌,王劲峰,张文忠，等.基于空间分析方法的中国区域差异研究.地理科学,2005,25(4):393-400
45.刘旭华,王劲峰.空间权重矩阵的生成方法分析与实验.地球信息科学,2002,2:38-44
46.李天生，周国法.空间自相关和分布型指数研究.生态学报,1994,14(3):327-331
47.刘永生，李瑞敏.不同方法下土壤重金属元素空间最大变异距离研究——以浙江上虞为例.岩矿测试,2007,26(4).
48.胡克林，张凤荣，吕贻忠，等．北京市大兴区土壤重金属含量的空间分布特征[J]．环境科学学报，2004，24(3)：463－468．
49.郑袁明，陈同斌，陈煌，等．北京市近郊区土壤镍的空间结构及分布特征[J]．地理学报，2003，58(3)：470－476．
50.张朝生,章申,何建邦.1998.长江水系沉积物重金属含量空间分布特征研究.空间自相关与分形方法[J].地理学报,53(1):87-96
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