메뉴 건너뛰기




Volumn 174, Issue 7, 2009, Pages 395-402

Comparison of sequential indicator simulation and transition probability indicator simulation used to model clay content in microscale surface soil

Author keywords

And stochastic simulation; Soil clay content; Spatial distribution; Transition probability Geostatistics

Indexed keywords

CLAY SOIL; COMPARATIVE STUDY; DATA ACQUISITION; ENVIRONMENTAL MANAGEMENT; GEOSTATISTICS; GRAIN SIZE; HISTOGRAM; QUANTITATIVE ANALYSIS; SIMULATION; SPATIAL DISTRIBUTION; STOCHASTICITY; VARIOGRAM;

EID: 68949178689     PISSN: 0038075X     EISSN: None     Source Type: Journal    
DOI: 10.1097/SS.0b013e3181aea77c     Document Type: Article
Times cited : (12)

References (27)
  • 1
    • 68949174171 scopus 로고    scopus 로고
    • Estimation of Available Water Capacity in Clay Soil by Using Pedo-transfer Functions
    • Bagheri, F., M. Bybordi, and H. A. Bahrami. 2005. Estimation of available water capacity in clay soil by using pedo-transfer functions. J. Agric. Sci. 1(6): 1-8.
    • (2005) J. Agric. Sci. , vol.1 , Issue.6 , pp. 1-8
    • Bagheri, F.1    Bybordi, M.2    Bahrami, H.A.3
  • 2
    • 41449102583 scopus 로고    scopus 로고
    • Comparison of indicator kriging, conditional indicator simulation and multiple-point statistics used to model slate deposits
    • Bastante, F. G., C. Ordóñez, J. Taboada, and J. M. Mat?́as. 2008. Comparison of indicator kriging, conditional indicator simulation and multiple-point statistics used to model slate deposits. Eng. Geol. 98:50-59.
    • (2008) Eng. Geol. , vol.98 , pp. 50-59
    • Bastante, F.G.1    Ordóñez, C.2    Taboada, X.3    Mat́as, J.M.4
  • 4
    • 0030455918 scopus 로고    scopus 로고
    • Transition probabilityYbased indicator geostatistics.
    • Carle, S. F., and G. E. Fogg. 1996. Transition probabilityYbased indicator geostatistics. Math Geol. 28(4):453-476.
    • (1996) Math Geol. , vol.28 , Issue.4 , pp. 453-476
    • Carle, S.F.1    Fogg, G.E.2
  • 5
    • 0031432328 scopus 로고    scopus 로고
    • Modeling spatial variability with one-and multi-dimensional continuous Markov chain
    • Carle, S. F., and G. E. Fogg. 1997. Modeling spatial variability with one-and multi-dimensional continuous Markov chain. Math. Geol. 29(7): 891-918.
    • (1997) Math. Geol. , vol.29 , Issue.7 , pp. 891-918
    • Carle, S.F.1    Fogg, G.E.2
  • 6
    • 33747826292 scopus 로고    scopus 로고
    • A sequential indicator simulation program for categorical variables with point and block data: BlockSIS
    • Deutsch, C. V 2006. A sequential indicator simulation program for categorical variables with point and block data: BlockSIS. Comput. Geosci. 32:1669-1681.
    • (2006) Comput. Geosci. , vol.32 , pp. 1669-1681
    • Deutsch, C.V.1
  • 7
    • 34250657015 scopus 로고    scopus 로고
    • Representative process samplingVin practice: Variographic analysis and estimation of total sampling errors (TSE)
    • Esbensen, K. H., H. H. Friis-Petersen, and L. Petersen, et al. 2007. Representative process samplingVin practice: Variographic analysis and estimation of total sampling errors (TSE). Chemometr. Intell. Lab. Syst. 88:41-59.
    • (2007) Chemometr. Intell. Lab. Syst. , vol.88 , pp. 41-59
    • Esbensen, K.H.1    Friis-Petersen, H.H.2    Petersen, L.3
  • 9
    • 0033242428 scopus 로고    scopus 로고
    • Impact of the simulation algorithm, magnitude of ergodic fluctuations and number of realizations on the spaces of uncertainty of flow properties
    • Goovaerts, P. 1999. Impact of the simulation algorithm, magnitude of ergodic fluctuations and number of realizations on the spaces of uncertainty of flow properties. Stoch. Environ. Res. Risk Assess. 13(3):161-182.
    • (1999) Stoch. Environ. Res. Risk Assess. , vol.13 , Issue.3 , pp. 161-182
    • Goovaerts, P.1
  • 10
    • 0033846316 scopus 로고    scopus 로고
    • Estimation or simulation of soil properties? An optimization problem with conflicting criteria.
    • Goovaerts, P. 2000. Estimation or simulation of soil properties? An optimization problem with conflicting criteria. Geoderma 97:165-186.
    • (2000) Geoderma , vol.97 , pp. 165-186
    • Goovaerts, P.1
  • 11
    • 34447527460 scopus 로고    scopus 로고
    • Methods to interpolate soil categorical variables from profile observations: Lessons from Iran.
    • Hengl, T., N. Toomanian, H. I. Reuter, and M. J. Malakouti. 2007. Methods to interpolate soil categorical variables from profile observations: Lessons from Iran. Geoderma 140:417-427.
    • (2007) Geoderma , vol.140 , pp. 417-427
    • Hengl, T.1    Toomanian, N.2    Reuter, H.I.3    Malakouti, M.X.4
  • 13
    • 33644531430 scopus 로고    scopus 로고
    • Effect of clay content and soil-water potential on mobilization and leaching of colloids in unsat-urated macroporous soil.
    • Kjaergaard, C., L. W. de. Jonge, and P. Moldrup. 2002. Effect of clay content and soil-water potential on mobilization and leaching of colloids in unsat-urated macroporous soil. DIAS Report. Plant Production 80:113-121.
    • (2002) DIAS Report. Plant Production , vol.80 , pp. 113-121
    • Kjaergaard, C.1    De. Jonge, L.W.2    Moldrup, P.3
  • 14
    • 34250652871 scopus 로고    scopus 로고
    • Geologic Heterogeneity and A Comparison of Two Geostatistical Models: Sequential Gaussian and Transition Probability-based Geostatistical Simulation
    • Lee, S. Y., S. F. Carle, and G. E. Fogg. 2007. Geologic heterogeneity and a comparison of two geostatistical models: Sequential Gaussian and transition probability-based geostatistical simulation. Adv. Water Resour. 30:1914-1932.
    • (2007) Adv. Water Resour. , vol.30 , pp. 1914-1932
    • Lee, S.Y.1    Carle, S.F.2    Fogg, G.E.3
  • 15
    • 33745114687 scopus 로고    scopus 로고
    • Transiogram: A spatial relationship measure for categorical data
    • Li, W. D. 2006. Transiogram: A spatial relationship measure for categorical data. Int. J. Geogr. Inf. Sci. 20(6):693-699.
    • (2006) Int. J. Geogr. Inf. Sci. , vol.20 , Issue.6 , pp. 693-699
    • Li, W.D.1
  • 16
    • 0033568784 scopus 로고    scopus 로고
    • Markov chain simulation of soil textural layers.
    • Li, W. D., B. G. Li, and Y C. Shi. 1999. Markov chain simulation of soil textural layers. Geoderma 92:37-53.
    • (1999) Geoderma , vol.92 , pp. 37-53
    • Li, W.D.1    Li, B.G.2    Shi, Y.C.3
  • 17
    • 33745853092 scopus 로고    scopus 로고
    • A generalized Markov chain approach for conditional simulation of categorical variables from grid samples.
    • Li, W. D., and C. R. Zhang. 2006. A generalized Markov chain approach for conditional simulation of categorical variables from grid samples. Trans. GIS 10(4):651-669.
    • (2006) Trans. GIS , vol.10 , Issue.4 , pp. 651-669
    • Li, W.D.1    Zhang, C.R.2
  • 18
    • 0031414956 scopus 로고    scopus 로고
    • Application of the Markov chain theory to describe spatial distribution of soil textural layers.
    • Li, W. D., C. R. Zhang, J. E. Burt, and A. X. Zhu. 1997. Application of the Markov chain theory to describe spatial distribution of soil textural layers. Soil Sci. 162:672-683.
    • (1997) Soil Sci. , vol.162 , pp. 672-683
    • Li, W.D.1    Zhang, C.R.2    Burt, J.E.3    Zhu, A.X.4
  • 19
    • 34249072264 scopus 로고    scopus 로고
    • Transiograms for characterizing spatial variability of soil classes
    • Li, W. D. 2007. Transiograms for characterizing spatial variability of soil classes. Soil Sci. Soc. Am. J. 71(3):881-893.
    • (2007) Soil Sci. Soc. Am. J. , vol.71 , Issue.3 , pp. 881-893
    • Li, W.D.1
  • 20
    • 0037297192 scopus 로고    scopus 로고
    • Relationships of soil respiration to microbial biomass, substrate availability and clay content.
    • Wang, W. J., R. C. Dalal, P. W. Moody, and C. J. Smith. 2003. Relationships of soil respiration to microbial biomass, substrate availability and clay content. Soil Biol. Biochem. 35(2):273-284.
    • (2003) Soil Biol. Biochem. , vol.35 , Issue.2 , pp. 273-284
    • Wang, W.J.1    Dalal, R.C.2    Moody, P.W.3    Smith, C.X.4
  • 21
    • 0022237883 scopus 로고
    • Quantitative spatial analysis of soil in the field.
    • Webster, R. 1985. Quantitative spatial analysis of soil in the field. Adv. Soil Sci. 3:1-70.
    • (1985) Adv. Soil Sci. , vol.3 , pp. 1-70
    • Webster, R.1
  • 22
    • 0034954394 scopus 로고    scopus 로고
    • PAH mobility in contaminated industrial: A Markov chain approach to the spatial variability of soil properties and PAH levels.
    • Weigand, H., K. U. Totsche, B. Huwe, and I. Kogel-Knabner. 2001. PAH mobility in contaminated industrial: A Markov chain approach to the spatial variability of soil properties and PAH levels. Geoderma 102:371-389.
    • (2001) Geoderma , vol.102 , pp. 371-389
    • Weigand, H.1    Totsche, K.U.2    Huwe, B.3    Kogel-Knabner, I.4
  • 23
    • 0033590145 scopus 로고    scopus 로고
    • Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework.
    • Weissmann, G. S., and G. E. Fogg. 1999. Multi-scale alluvial fan heterogeneity modeled with transition probability geostatistics in a sequence stratigraphic framework. J. Hydrology 226:48-65.
    • (1999) J. Hydrology , vol.226 , pp. 48-65
    • Weissmann, G.S.1    Fogg, G.E.2
  • 24
    • 38549145991 scopus 로고    scopus 로고
    • Near infrared reflectance spectroscopy compared with soil clay and organic matter content for estimating within-field variation in N uptake in cereals.
    • Wetterlind, J., B. Stenberg, and A. Jonsson. 2008. Near infrared reflectance spectroscopy compared with soil clay and organic matter content for estimating within-field variation in N uptake in cereals. Plant Soil 302(1-2):3 17-327.
    • (2008) Plant Soil , vol.302 , Issue.1-2 , pp. 317-327
    • Wetterlind, J.1    Stenberg, B.2    Jonsson, A.3
  • 25
    • 0024165388 scopus 로고
    • The use of variograms in remote sensing: II. Real digital images. Remote Sens
    • Woodcock, C. E., A. H. Strahler, and D. L. B. Jupp. 1988. The use of variograms in remote sensing: II. Real digital images. Remote Sens. Environ. 25:349-379.
    • (1988) Environ. , vol.25 , pp. 349-379
    • Woodcock, C.E.1    Strahler, A.H.2    Jupp, D.L.B.3
  • 26
    • 1542291102 scopus 로고    scopus 로고
    • An efficient Markov chain model for the simulation of heterogeneous soil structure
    • Wu, K., N. Nunan, J. W Crawford, L. M. Young, and K. Ritz. 2004. An efficient Markov chain model for the simulation of heterogeneous soil structure. Soil Sci. Soc. Am. J. 68:346-351.
    • (2004) Soil Sci. Soc. Am. J. , vol.68 , pp. 346-351
    • Wu, K.1    Nunan, N.2    Crawford, J.W.3    Young, L.M.4    Ritz, K.5
  • 27
    • 50249146342 scopus 로고    scopus 로고
    • Regional-scale modelling of the spatial distribution of surface and subsurface textural classes in alluvial soils using Markov chain geostatistics
    • Zhang, C., and W D. Li. 2008. Regional-scale modelling of the spatial distribution of surface and subsurface textural classes in alluvial soils using Markov chain geostatistics. Soil Use Manag. 24:263-272.
    • (2008) Soil Use Manag. , vol.24 , pp. 263-272
    • Zhang, C.1    Li., W.D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.