自然资源学报 ›› 2012, Vol. 27 ›› Issue (1): 163-175.doi: 10.11849/zrzyxb.2012.01.017
• 专题论坛 • 上一篇
史文娇1, 岳天祥1, 石晓丽2,3, 宋伟1
收稿日期:
2011-05-10
修回日期:
2011-07-20
出版日期:
2012-01-20
发布日期:
2012-01-20
作者简介:
史文娇(1982- ),女,辽宁葫芦岛人,博士,研究方向为土壤属性空间模拟、全球变化与区域农业。E-mail: shiwj@lreis.ac.cn
基金资助:
国家自然科学基金青年基金项目(41001057);国家杰出青年科学基金项目(40825003);地表过程与资源生态国家重点实验室开放基金项目(2011-KF-06)。
SHI Wen-jiao1, YUE Tian-xiang1, SHI Xiao-li2,3, SONG Wei1
Received:
2011-05-10
Revised:
2011-07-20
Online:
2012-01-20
Published:
2012-01-20
摘要: 作为土壤变化的时空定量监测方法,土壤属性空间插值方法及其精度是计量土壤学和"数字土壤"领域的重要研究内容。文章首先介绍了土壤属性空间插值的常用方法,包括克立格插值法(Kriging)、反距离权重法(IDW)、样条插值法(Spline)、贝叶斯最大熵(BME)、地理加权回归(GWR)以及高精度曲面建模方法(HASM);其次阐述了土壤属性空间插值精度验证的方法和指标;再次总结了能够提高土壤属性插值精度的6种途径,包括合理选择插值方法、准确设定插值方法参数、合理设计采样数目和密度、注意空间自相关程度和范围的影响、科学安排实验分析顺序以及结合辅助信息进行插值;最后从插值方法的选择、验证指标的选取以及辅助信息的结合三个方面指出了土壤属性空间插值方法及其精度的未来研究方向。
中图分类号:
S159
史文娇, 岳天祥, 石晓丽, 宋伟. 土壤连续属性空间插值方法及其精度的研究进展[J]. 自然资源学报, 2012, 27(1): 163-175.
SHI Wen-jiao, YUE Tian-xiang, SHI Xiao-li, SONG Wei. Research Progress in Soil Property Interpolators and Their Accuracy[J]. JOURNAL OF NATURAL RESOURCES, 2012, 27(1): 163-175.
[1] 史舟, Lark R M. 土壤学的新分支——计量土壤学 (Pedometrics) 的形成与发展[J]. 土壤学报, 2007, 44(5): 919-924. [2] 史学正, 于东升. "数字土壤"——21世纪土壤学面临的机遇与挑战[J]. 土壤通报, 2000, 31(3): 104-106, 121. [3] 赵其国. 土壤科学发展的战略思考[J]. 土壤, 2009, 41(5): 681-688. [4] Zhao Y C, Shi X Z, Yu D S, et al. Uncertainty assessment of spatial patterns of soil organic carbon density using sequential indicator simulation: A case study of Hebei province, China [J]. Chemosphere, 2005, 59(11): 1527-1535. [5] Mueller T G, Pierce F J, Schabenberger O, et al. Map quality for site-specific fertility management [J]. Soil Science Society of America Journal, 2001, 65(5): 1547-1558. [6] 史文娇, 魏丹, 汪景宽, 等. 双城市土壤重金属空间分异及影响因子分析[J]. 水土保持学报, 2007, 21(1): 59-64. [7] Pierce F J, Nowak P. Aspects of precision agriculture [J]. Advances in Agronomy, 1999, 67: 1-85. [8] Panagopoulos T, Jesus J, Antunes M D C, et al. Analysis of spatial interpolation for optimising management of a salinized field cultivated with lettuce [J]. European Journal of Agronomy, 2006, 24(1): 1-10. [9] Mueller T G, Pierce F J. Soil carbon maps: Enhancing spatial estimates with simple terrain attributes at multiple scales [J]. Soil Science Society of America Journal, 2003, 67(1): 258-267. [10] 王政权. 地统计学及其在生态学中的应用[M]. 北京: 科学出版社, 1999. [11] Deutsch C V, Journel A G. GSLIB: Geostatistical Software Library and User's Guide [M]. New York: Oxford University Press, 1998. [12] Wackernagel H. Multivariate Geostatistics: An Introduction with Applications [M]. Berlin: Springer, 1998. [13] Chiles J P, Delfiner P. Geostatistics: Modeling Spatial Uncertainty [M]. New York: Wiley, 1999. [14] Odeh I O A, McBratney A B, Chittleborough D J. Spatial prediction of soil properties from landform attributes derived from a digital elevation model [J]. Geoderma, 1994, 63(3/4): 197-214. [15] Odeh I O A, McBratney A B, Chittleborough D J. Further results on prediction of soil properties from terrain attributes: Heterotopic Co-Kriging and regression-Kriging [J]. Geoderma, 1995, 67(3/4): 215-226. [16] Shi W, Liu J, Du Z, et al. Surface modelling of soil properties based on land use information [J]. Geoderma, 2011, 162: 347-357. [17] Stein A, Hoogerwerf M, Bouma J. Use of soil-map delineations to improve (Co-) Kriging of point data on moisture deficits [J]. Geoderma, 1988, 43(2/3): 163-177. [18] Voltz M, Webster R. A comparison of Kriging, cubic splines and classification for predicting soil properties from sample information [J]. European Journal of Soil Science, 1990, 41(3): 473-490. [19] 史舟, 李艳. 地统计学在土壤学中的应用[M]. 北京: 中国农业出版社, 2006. [20] Robinson T P, Metternicht G. Testing the performance of spatial interpolation techniques for mapping soil properties [J]. Computers and Electronics in Agriculture, 2006, 50(2): 97-108. [21] Webster R, Oliver M A. Geostatistics for Environmental Scientists [M]. West Sussex, England: John Wiley and Sons, 2001. [22] Christakos G. A Bayesian/maximum-entropy view to the spatial estimation problem [J]. Mathematical Geology, 1990, 22(7): 763-777. [23] Christakos G. Modern Spatiotemporal Geostatistics [M]. New York: Oxford University Press, 2000. [24] D'Or D, Bogaert P. Continuous-valued map reconstruction with the Bayesian Maximum Entropy [J]. Geoderma, 2003, 112(3/4): 169-178. [25] D'Or D, Bogaert P, Christakos G. Application of the BME approach to soil texture mapping [J]. Stochastic Environmental Research and Risk Assessment, 2001, 15(1): 87-100. [26] Brus D, Bogaert P, Heuvelink G. Bayesian Maximum Entropy prediction of soil categories using a traditional soil map as soft information [J]. European Journal of Soil Science, 2008, 59(2): 166-177. [27] Douaik A, Van Meirvenne M, Toth T. Soil salinity mapping using spatio-temporal Kriging and Bayesian maximum entropy with interval soft data [J]. Geoderma, 2005, 128(3/4): 234-248. [28] Lee S J, Wentz E A. Applying Bayesian maximum entropy to extrapolating local-scale water consumption in Maricopa County, Arizona [J]. Water Resources Research, 2008, 44(1): W01401. [29] Bogaert P. Spatial prediction of categorical variables: The Bayesian maximum entropy approach [J]. Stochastic Environmental Research and Risk Assessment, 2002, 16(6): 425-448. [30] 罗明, 裴韬. 空间软数据及其插值方法研究进展[J]. 地理科学进展, 2009, 28(5): 663-672. [31] 张贝, 李卫东, 杨勇, 等. 贝叶斯最大熵地统计学方法及其在土壤和环境科学上的应用[J]. 土壤学报, 2011, 48(4): 831-839. [32] Bogaert P, D'Or D. Estimating soil properties from thematic soil maps: The Bayesian Maximum Entropy approach [J]. Soil Science Society of America Journal, 2002, 66(5): 1492-1500. [33] Brunsdon C, Fotheringham A S, Charlton M E. Geographically weighted regression: A method for exploring spatial nonstationarity [J]. Geographical analysis, 1996, 28(4): 281-298. [34] Mishra U, Lal R, Liu D, et al. Predicting the spatial variation of the soil organic carbon pool at a regional scale [J]. Soil Science Society of America Journal, 2010, 74(3): 906-914. [35] Fotheringham A S, Brunsdon C, Charlton M. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships [M]. Chichester, UK: John Wiley & Sons Ltd., 2002. [36] Charlton M, Fotheringham S, Brunsdon C. GWR 3 Software for geographically weighted regression [M]. Newcastle upon Tyne, UK: Spatial Analysis Research Group, Department of Geography, University of Newcastle upon Tyne, 2003. [37] Yue T X, Du Z P, Song D J, et al. A new method of surface modeling and its application to DEM construction [J]. Geomorphology, 2007, 91(1/2): 161-172. [38] Yue T X, Du Z P, Song Y J. Ecological models: Spatial models and Geographic Information Systems[M]//Jrgensen S E, Fath B. Encyclopedia of Ecology. England: Elsevier Limited, 2008: 3315-3325. [39] Yue T X, Song Y J. The YUE-HASM Method//Li D, Ge Y, Foody G M. Proceeding of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences. Shanghai, 2008: 148-153. [40] Yue T X, Wang S H. Adjustment computation of HASM: A high-accuracy and high-speed method [J]. International Journal of Geographical Information Science, 2010, 24(11): 1725-1743. [41] Yue T X, Song D J, Du Z P, et al. High-accuracy surface modelling and its application to DEM generation [J]. International Journal of Remote Sensing, 2010, 31(8): 2205-2226. [42] Yue T X. Surface Modelling: High Accuracy and High Speed Methods [M]. New York: CRC Press, 2011. [43] Shi W J, Liu J Y, Du Z P, et al. Surface modelling of soil pH [J]. Geoderma, 2009, 150(1/2): 113-119. [44] Shi W J, Liu J Y, Du Z P, et al. Surface modelling of soil properties based on land use information [J]. Geoderma, 2011, 162(3/4): 347-357. [45] 史文娇, 杜正平, 宋印军, 等. 基于多重网格求解的土壤属性高精度曲面建模研究[J]. 地理研究, 2011, 30(5): 941-950. [46] 李启权, 岳天祥, 范泽孟, 等. 中国表层土壤有机质空间分布模拟分析方法研究[J]. 自然资源学报, 2010, 25(8): 1385-1399. [47] 李启权, 岳天祥, 范泽孟, 等. 中国表层土壤全氮的空间模拟分析[J]. 地理研究, 2010, 29(11): 1981-1992. [48] Davis B M. Uses and abuses of cross-validation in geostatistics [J]. Mathematical Geology, 1987, 19(3): 241-248. [49] Olea R A. Geostatistics for Engineers and Earth Scientists [M]. Dordrecht: Kluwer Academic Publishers, 1999. [50] Tomczak M. Spatial interpolation and its uncertainty using automated anisotropic inverse distance weighting (IDW)-cross-validation/Jackknife approach [J]. Journal of Geographic Information and Decision Analysis, 1998, 2(2): 18-30. [51] Tabios G Q, Salas J D. A comparative analysis of techniques for spatial interpolation of precipitation [J]. Journal of the American Water Resources Association, 1985, 21(3): 365-380. [52] Hosseini E, Gallichand J, Marcotte D. Theoretical and experimental performance of spatial interpolation methods for soil-salinity analysis [J]. Transactions of the American Society of Agricultural Engineers, 1994, 37(6): 1799-1807. [53] Kravchenko A, Bullock D G. A comparative study of interpolation methods for mapping soil properties [J]. Agronomy Journal, 1999, 91(3): 393-400. [54] Schloeder C A, Zimmerman N E, Jacobs M J. Comparison of methods for interpolating soil properties using limited data [J]. Soil Science Society of America Journal, 2001, 65(2): 470-479. [55] Laslett G M, McBratney A B, Pahl P J, et al. Comparison of several spatial prediction methods for soil pH [J]. Journal of Soil Science, 1987, 38(2): 325-341. [56] Mueller T G, Pusuluri N B, Mathias K K, et al. Site-specific soil fertility management: A model for map quality [J]. Soil Science Society of America Journal, 2004, 68(6): 2031-2041. [57] Liu T L, Juang K W, Lee D Y. Interpolating soil properties using Kriging combined with categorical information of soil maps [J]. Soil Science Society of America Journal, 2006, 70(4): 1200-1209. [58] Johnston K. Using ArcGIS Geostatistical Analyst [M]. California: ESRI, 2001. [59] Zhang R, Myers D E, Warrick A W. Estimation of the spatial distribution of soil chemicals using pseudo-cross-variograms [J]. Soil Science Society of America Journal, 1992, 56(5): 1444-1452. [60] Gotway C A, Ferguson R B, Hergert G W, et al. Comparison of Kriging and inverse-distance methods for mapping soil parameters [J]. Soil Science Society of America Journal, 1996, 60(4): 1237-1247. [61] Kravchenko A N. Influence of spatial structure on accuracy of interpolation methods [J]. Soil Science Society of America Journal, 2003, 67(5): 1564-1571. [62] Agterberg F P. Trend surface analysis //Gaile G L, Willmott C J. Spatial Statistics and Models. Dordrecht, the Netherlands: Reidel, 1984: 147-171. [63] Triantafilis J, Odeh I O A, McBratney A B. Five geostatistical models to predict soil salinity from electromagnetic induction data across irrigated cotton [J]. Soil Science Society of America Journal, 2001, 65(3): 869-878. [64] Leenaers H, Okx J P, Burrough P A. Comparison of spatial prediction methods for mapping floodplain soil pollution [J]. Catena, 1990, 17(6): 535-550. [65] Weber D, Englund E. Evaluation and comparison of spatial interpolators [J]. Mathematical Geology, 1992, 24(4): 381-391. [66] Wollenhaupt N C, Wolkowski R P, Clayton M K. Mapping soil test phosphorus and potassium for variable-rate fertilizer application [J]. Journal of Production Agriculture, 1994, 7(4): 441-447. [67] Kollias V J, Kalivas D P, Yassoglou N J. Mapping the soil resources of a recent alluvial plain in Greece using fuzzy sets in a GIS environment [J]. European Journal of Soil Science, 1999, 50(2): 261-273. [68] Isaaks E H, Srivastava R M. An Introduction to Applied Geostatistics [M]. New York: Oxford University Press, 1989. [69] Weber D D, Englund E J. Evaluation and comparison of spatial interpolators II [J]. Mathematical Geology, 1994, 26(5): 589-603. [70] Webster R, Oliver M A. Sample adequately to estimate variograms of soil properties [J]. Journal of Soil Science, 1992, 43(1): 177-192. [71] Flatman G T, Yfantis A A . Geostatistical sampling designs for hazardous waste sites . Washington, DC: ACS, 1996. [72] Sadler E J, Busscher W J, Bauer P J, et al. Spatial scale requirements for precision farming: A case study in the South Eastern USA [J]. Agronomy Journal, 1998, 90(2): 191-197. [73] Goovaerts P. Geostatistics in soil science: State-of-the-art and perspectives [J]. Geoderma, 1999, 89(1/2): 1-45. [74] Bishop T F A, McBratney A B. A comparison of prediction methods for the creation of field-extent soil property maps [J]. Geoderma, 2001, 103(1/2): 149-160. [75] Florinsky I V, Eilers R G, Manning G R, et al. Prediction of soil properties by digital terrain modelling [J]. Environmental Modelling & Software, 2002, 17(3): 295-311. [76] Chen F, Kissel D E, West L T, et al. Field-scale mapping of surface soil organic carbon using remotely sensed imagery [J]. Soil Science Society of America Journal, 2000, 64(2): 746-753. [77] Takata Y, Funakawa S, Akshalov K, et al. Spatial prediction of soil organic matter in northern Kazakhstan based on topographic and vegetation information [J]. Soil Science and Plant Nutrition, 2007, 53(3): 289-299. [78] Knotters M, Brus D J, Oude Voshaar J H. A comparison of Kriging, co-Kriging and Kriging combined with regression for spatial interpolation of horizon depth with censored observations [J]. Geoderma, 1995, 67(3/4): 227-246. [79] Triantafilis J, Huckel A I, Odeh I O A. Comparison of statistical prediction methods for estimating field-scale clay content using different combinations of ancillary variables [J]. Soil Science, 2001, 166(6): 415-427. [80] Triantafilis J, Odeh I O A, Warr B, et al. Mapping of salinity risk in the lower Namoi valley using non-linear Kriging methods [J]. Agricultural Water Management, 2004, 69(3): 203-229. [81] Odeh I O A, McBratney A B, Chittleborough D J. Spatial prediction of soil properties from landform attributes derived from a digital elevation model [J]. Geoderma, 1994, 63(3/4): 197-214. [82] Juang K W, Lee D Y. A comparison of three Kriging methods using auxiliary variables in heavy-metal contaminated soils [J]. Journal of Environmental Quality, 1998, 27(2): 355-363. [83] D'Acqui L P, Santi C A, Maselli F. Use of ecosystem information to improve soil organic carbon mapping of a Mediterranean Island [J]. Journal of Environmental Quality, 2007, 36(1): 262-271. [84] Wu C F, Wu J P, Luo Y M, et al. Statistical and geoestatistical characterization of heavy metal concentrations in a contaminated area taking into account soil map units [J]. Geoderma, 2008, 144(1/2): 171-179. [85] Oberthür T, Goovaerts P, Dobermann A. Mapping soil texture classes using field texturing, particle size distribution and local knowledge by both conventional and geostatistical methods [J]. European Journal of Soil Science, 1999, 50(3): 457-479. [86] Carre F, Girard M C. Quantitative mapping of soil types based on regression Kriging of taxonomic distances with landform and land cover attributes [J]. Geoderma, 2002, 110(3/4): 241-263. |
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