Fuzzy inference of soil patterns: Implications for watershed modeling

Geophysical Monograph Series

Volumn 108, Issue , 1998, Pages 135-149

  Zhu, A Xing ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85040534195     PISSN: 00658448     EISSN: 23288779     Source Type: Book Series    
DOI: 10.1029/GM108p0135     Document Type: Chapter

References (54)

1. Band, L.E., D.L. Peterson, S.W. Running, J. Coughlan, R. Lammers, J. Dungan, and R. Nemani, Forest ecosystem processes at the watershed scale: basis for distributed simulation. Ecological Modelling, 56, 171-196, 1991.
2. Band, L.E., Spatial aggregation of complex terrain, Geographic Analysis, 21, 279-293, 1989.
3. Band, L.G., and I.D. Moore, Scale: Landscape attributes and geographical information systems, Hydrological Processes, 9, 401-422, 1995.
4. Bezdek, J.C., R. Ehrlich, and W. Full, The fuzzy c-means clustering algorithm, Computers & Geosciences, 10, 191-203, 1984.
5. Bierkens, M.F., and P.A. Burrough, The indicator approach to categorical soil data: II. Application to mapping and land use suitability analysis, Journal of Soil Science, 44, 369-381, 1993.
6. Bregt, A.K., Processing of Soil Survey Data, Wageningen Agricultural University, Wageningen, The Netherlands, 1992.
7. Burgess, T.M., and R. Webster, Optimal interpolation and isarithmic mapping of soil properties: I. The semi-variogram and punctual kriging, Journal of Soil Science, 31, 315-331, 1980.
8. Burrough, P.A., Fuzzy mathematical methods for soil survey and land evaluation, Journal of Soil Science, 40, 477-492, 1989.
9. Burrough, P.A., Soil variability: a late 20th century view, Soils and Fertilizers, 56, 529-562, 1993.
10. Burrough, P.A., Opportunities and limitations of GIS-based modeling of solute transport at the regional scale, in Applications of GIS to the Modeling of Non-point Source Pollutants in the Vadose Zone, edited by D.L. Corwin and K. Loague, pp. 19-38, SSSA Special Publication No. 48, SSSA, Madison, WI. 1996.
11. Burrough, P.A., R.A. MacMillan, and W. Van Deursen, Fuzzy classification methods for determining land suitability from soil profile observations, Journal of Soil Science, 43, 193-210, 1992.
12. Burrough, P.A. P. Van Gaans, and R. Hootsmans, Continuous classification in soil survey: spatial correlation, confusion and boundaries, Geoderma, 77, 115-135, 1997.
13. Chow, V.T., D.R. Maidment, and L.W. Mays, Applied Hydrology, McGraw-Hill, New York. 1988.
14. Corwin, D.L. GIS applications of deterministic solute transport models for regional-scale assessment of non-point source pollutants in the vadose zone, in Applications of GIS to the Modeling of Non-point Source Pollutants in the Vadose Zone, edited by D.L. Corwin and K. Loague, pp. 69-100, SSSA Special Publication No. 48, SSSA, Madison, WI. 1996.
15. Corwin, D.L., P.J. Vaughan, and K. Loague, Modeling nonpoint source pollutants in the vadose zone with GIS, Environmental Science & Technology, 31, 2157-2175, 1997.
16. De Gruijter, J.J., D.J.J. Walvoort, and P.F.M. Van Gaans, Continuous soil maps: a fuzzy set approaches to bridge the gap between aggregation levels of process and distribution models, Geoderma, 77, 169-195, 1992.
17. Ellsworth, T.R. Influence of transport variability structure on parameter estimation and model discrimination, in Applications of GIS to the Modeling of Non-point Source Pollutants in the Vadose Zone, edited by D.L. Corwin and K. Loague, pp. 101130, SSSA Special Publication No. 48, SSSA, Madison, WI. 1996.
18. Ferguson, R.B. and G.W. Hergert, Sampling and spatial analysis techniques for quantifying soil map unit composition, this volume, in press, 1998.
19. Gessler, P.E., Moore, I.D., Mckenzie, N.J., and Ryan, P.J., Soil-landscape modelling and spatial prediction of soil attributes, International Journal of Geographical Information Systems., 9, 421-432, 1995.
20. Goodchild, M.F., Geographical data modeling, Computers & Geosciences, 18, 401-408, 1992.
21. Jenny, H., The Soil Resource: Origin and Behavior, Springer, New York, 1980.
22. Jenny, H., Factors of Soil Formation: A System of Quantitative Pedology, McGraw-Hill, New York, 1994.
23. Joumel, A.G., Geostatistics: models and tools for the earth sciences. Mathematical Geology, 18, 119-140, 1986.
24. Jury, W.A., Stochastic solute transport modeling trends and their potential compatibility with GIS, in Applications of GIS to the Modeling of Non-Point Source Pollutants in the Vadose Zone, edited by D.L. Corwin and K. Loague, pp. 57-68, SSSA Special Publication No. 48, SSSA, Madison, WI, 1996.
25. Jury, W.A., Spatial variability of soil properties, in Vadose Zone Modeling of Organic Pollutants, edited by S.C. Hem and S.M. Melancon, pp. 245-269, Lewis Publication, Chelsea, MI, 1985.
26. Lagacherie, P., D.R. Cazemire, P. Van Gaans, and P.A. Burrough, Fuzzy k-means clustering of fields in an elementary catchement and extrapolation to a larger area, Geoderma, 77, 197-216, 1997.
27. Loague, K. Soil water content at R-5. Part 1. Spatial and temporal variability, Journal of Hydrology, 139, 233-251, 1992.
28. Lytle, D.L., Digital soils databases for the United States, in Environmental Modeling with GIS, edited by Michael F. Goodchild, Bradley O. Parks, and Louis T. Steyaert, pp. 386391, Oxford University Press, New York, 1993.
29. Maclean, A.L., T.P. D’Avello, and S.G. Shetron, The use of variability diagrams to improve the interpretation of digital soil maps in a GIS, Photogrammetric Engineering & Remote Sensing, 59, 223-228, 1993.
30. Mark, D.M., and F. Csillag, The nature of boundaries on ‘area-class’ maps, Cartographica, 27, 56-78, 1989.
31. Maidment, D.R. GIS and hydrologic modeling, in Environmental Modeling with GIS, edited by Michael F. Goodchild, Bradley O. Parks, and Louis T. Steyaert, pp. 147-167, Oxford University Press, New York, 1993.
32. McBratney, A.B., and J.J. De Gruijter, A continuum approach to soil classification by modified fuzzy k-means with extragrades, Journal of Soil Science, 43, 159-175, 1992.
33. McBratney, A.B., and I.O.A. Odeh., Application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions, Geoderma, 77, 85-113, 1997.
34. McBratney, A.B., and R. Webster, Choosing functions for semivariograms of soil properties and fitting them to sampling estimates, Journal of Soil Science, 37, 617-639, 1986.
35. Moore, I.D., P. E. Gessler, G.A. Nielsen, and G.A. Peterson, Soil attribute prediction using terrain analysis, Soil Science Society of America Journal, 57, 443-452, 1993.
36. Nielsen, R.D., R.J. Bigler, T. Sobecki, and D.J. Lytle. Applications of soil survey attribute data to GIS pollution assessment models, in Applications of GIS to the Modeling of Non-point Source Pollutants in the Vadose Zone, edited by D.L. Corwin and K. Loague, pp. 175-183, SSSA Special Publication No. 48, SSSA, Madison, WI. 1996.
37. Nimlos, J.T., Soils of Lubrecht Experimental Forest. Miscellaneous Publication No. 44, Montana Forest and Conservation Experiment Station, Missoula, Montana, 1986.
38. Odeh, I.O.A., A.B. McBratney, and D.J. Chittleborough, Soil pattern recognition with fuzzy-c-means: Application to classification and soil-landform interrelationships, Soil Science Society of American Journal, 56, 505-516, 1992a.
39. Odeh, I.O.A., A.B. McBratney, and D.J. Chittleborough, Fuzzy-c-Means and kriging for mapping soil as a continuous system., Soil Science Society of American Journal, 56, 1848-1854, 1992b.
40. Rogowski, A.S., Quantifying soil variability in GIS applications: II spatial distribution of soil properties, International Journal of Geographical Information Systems., 10, 455-475, 1996.
41. Rumelhart, D.E., G.E. Hinton, and R.J. Williams, Learning internal representations by error propagation, in Parallel Distributed Processing - Explorations in the Microstructure of Cognition Vol. I, edited by D.E. Rumelhart, J.L. McClelland, The MIT Press, Massachusetts, pp. 318-362, 1986.
42. Wang, F., Fuzzy supervised classification of remote sensing images, IEEE Transactions on Geoscience and remote sensing, 28, 194-201, 1990.
43. Warrick, A.W., and D.R. Nielsen, Spatial variability of soil physical properties in the field, in Applications of Soil Physics, edited by D. Hillel, pp. 319-344, Academic Press, New York, 1980.
44. Webster, R., Local disjunctive kriging of soil properties with change of support, Journal of Soil Science, 42, 301-318, 1991.
45. Webster, R., and A.B. McBratney, On the Akaike information criterion for choosing models for variograms of soil properties, Journal of Soil Science, 40, 493-496, 1989.
46. Webster R., and M.A. Oliver, Optimal interpolation and isarithmic mapping of soil properties: VI disjunctive kriging and mapping the conditional probability, Journal of Soil Science, 40, 497-512, 1989.
47. Zhang, R, S. Rahman, G.F. Vance, and L.C. Munn, Geostatistical analyses of trace elements in soils and plants, Soil Science, 159, 383-390, 1995.
48. White, I., Measurement of soil physical properties in the field, in Flow and Transport in the Natural Environment: Advances and Applications, edited by W.L. Steffen and O.T. Denmead, pp. 5985, Springer-Verlag, Berlin, 1988.
49. Yost, RS., X. Wang, C.S. Smith, R.E. Green, and C. Sangchyoswat, Incorporating spatial variability into existing soils databases, this volume, in press, 1998.
50. Zhu, A.X., A knowledge-based approach in environment management, in Proceedings of Geoinformatics '95, edited by T. Fung and H. Lin, p. 100-110, May 26-28, 1995, The Chinese University of Hong Kong, Hong Kong, 1995.
51. Zhu, A.X., A similarity model for representing soil spatial information, Geoderma, 77, 217-242, 1997.
52. Zhu, A.X., and L.E. Band, A knowledge-based approach to data integration for soil mapping, Canadian Journal of Remote Sensing, 20, 408-418, 1994.
53. Zhu, A.X., L.E. Band, B. Dutton, and T.J. Nimlos, Automated soil inference under fuzzy logic, Ecological Modelling, 90, 123-145, 1996.
54. Zhu, A.X., L.E. Band, R. Vertessy, and B. Dutton, Derivation of soil properties using a soil land inference model (SoLIM), Soil Science Society of America Journal, 61, 523-533, 1997.