Geospatial Mapping of Soil Nitrate-Nitrogen Distribution Under a Mixed-Land Use System

Pedosphere

Volumn 19, Issue 4, 2009, Pages 434-445

  LAMSAL, S ^a   BLISS, C M ^b   GRAETZ, D A ^c  

^a UNIVERSITY OF FLORIDA   (United States)

^b USDA FOREST SERVICE   (United States)

^c UNIVERSITY OF FLORIDA   (United States)

Author keywords

environmental correlation; general linear model; kriging; land use; regression

Indexed keywords

ENVIRONMENTAL MODELING; ENVIRONMENTAL RISK; GROUNDWATER; KRIGING; LAND USE; LEACHING; MAPPING METHOD; SOIL NITROGEN; SPATIAL DISTRIBUTION;

FLORIDA [UNITED STATES]; NORTH AMERICA; UNITED STATES;

EID: 67649965352     PISSN: 10020160     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1002-0160(09)60136-3     Document Type: Article

References (32)

1. Anselin L. Local indicators of spatial association-LISA. Geogr. Anal. 27 (1995) 93-115
2. Bishop T.F.A., and Minasny B. Digital soil-terrain modeling: The predictive potential and uncertainty. In: Grunwald S. (Ed). Environmental Soil-Landscape Modeling (2006), CRC Press, Boca Raton, FL
3. Breiman L., Friedman J., Olshen R., and Stone C. Classification and Regression Trees (1984), Wadsworth, Pacific Grove, CA
4. Burgess T.M., and Webster R. Optimal interpolation and isarithmic mapping of soil properties: I. The semivariogram and punctual kriging. J. Soil Sci. 31 (1980) 315-331
5. De'Ath G., and Fabricius K.E. Classification and regression trees: A powerful yet simple technique for ecological data analysis. Ecology. 81 11 (2000) 3178-3192
6. Dobos E., Micheli E., Baumgardner M.F., Biehl L., and Helt T. Use of combined digital elevation model and satellite radiometric data for regional soil mapping. Geoderma. 97 (2000) 367-391
7. Douaoui A.E.K., Nicolas H., and Walter C. Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data. Geoderma. 134 (2006) 217-230
8. Florida Department of Transportation (FDOT). Florida Land Use, Cover and Forms Classification System. 3rd Edition (1999), Department of Transportation, State of Florida, Tallahassee, FL
9. Ge S., and Sun B. Spatial and temporal changes of soil inorganic nitrogen in rice-wheat rotation system at county scale-A case study in Yizheng County, Jiangsu Province, China. J. Agro-Environ. Sci. 28 2 (2008) 636-642 (in Chinese).
10. Gessler P.E., Moore I.D., McKenzie N.J., and Ryan P.J. Soil-landscape modeling and spatial prediction of soil attributes. Int. J. Geogr. Inf. Syst. 9 4 (1995) 421-432
11. Gessler P.E., Chadwick O.A., Chamran F., Althouse L., and Holmes K. Modeling soil-landscape and ecosystem properties using terrain attributes. Soil Sci. Soc. Am. J. 64 (2000) 2046-2056
12. Goodchild M.F. Spatial Autocorrelation, Concepts and Techniques in Modern Geography (CATMOG) 47 (1986), Geo Books, Norwich, UK
13. Goovaerts P. Geostatistics for Natural Resources Evaluation (1997), Oxford University Press, New York
14. Hengl T., Heuvelink G.B.M., and Stein A. A generic framework for spatial prediction of soil variables based on regression-kriging. Geoderma. 120 (2004) 75-93
15. Lamsal S., Grunwald S., Bruland G.L., Bliss C.M., and Comerford N.B. Regional hybrid geospatial modeling of soil nitrate-nitrogen in the Santa Fe River Watershed. Geoderma. 135 (2006) 233-247
16. Lesch S.M., Strauss D.J., and Rhoades J.D. Spatial prediction of soil salinity using electromagnetic induction techniques: 1. Statistical prediction models: a comparison of multiple linear regression and cokriging. Water Resource. Res. 31 (1995) 373-386
17. Lillesand T.M., and Kiefer R.W. Remote sensing and image interpretation (2000), John Wiley & Sons, Inc., New York
18. McBratney A.B., Santos M.L.M., and Minasny B. On digital soil mapping. Geoderma. 117 (2003) 3-52
19. McBratney A.B., Odeh I.O.A., Bishop T.F.A., Dunbar M.S., and Shatar T.M. An overview of pedometric techniques for use in soil survey. Geoderma. 97 (2000) 293-327
20. McBratney A.B., and Pringle M.J. Estimating average and proportional variograms of soil properties and their potential use in precision agriculture. Prec. Agr. 1 (1999) 125-152
21. McKenzie N.J., Gessler P.E., Ryan P.J., and O'Connel D.A. The role of terrain analysis in soil mapping. In: Wilson J.P., and Gallant J.C. (Eds). Terrain Analysis (2000), John Wiley and Sons, New York
22. McKenzie N.J., and Ryan P.J. Spatial prediction of soil properties using environmental correlation. Geoderma. 89 (1999) 67-94
23. Odeh I.O.A., McBratney A.B., and Chittleborough D.J. Further results on prediction of soil properties form terrain attributes: Heterotrophic cokriging and regression-kriging. Geoderma. 67 (1995) 215-226
24. Pannatier Y. Variowin: Software for Spatial Data Analysis in 2D (1996), Springer-Verlag, New York, NY
25. Pierzynski G.M., Sims J.T., and Vance G.F. Soils and Environmental Quality (1994), Lewis Publishers, Boca Raton, FL
26. Rivero R.G., Grunwald S., and Bruland G.L. Incorporation of spectral data into multivariate geostatistical models to map soil phosphorus variability in a Florida wetland. Geoderma. 140 (2007) 428-443
27. Shahandeh H., Wright A.L., Hons F.M., and Lascano R.J. Spatial and temporal variation of soil nitrogen parameters related to soil texture and corn yield. Agron. J. 97 (2005) 772-782
28. Steinberg D., and Colla P. CART: Tree-Structured Non-Parametric Data Analysis (1995), Salford Systems, San Diego, CA
29. Stenger R., Priesack E., and Beese F. Spatial variation of nitrate-N and related soil properties at the plot-scale. Geoderma. 105 (2002) 259-275
30. United States Department of Agriculture, and Natural Resources Conservation Service (USDA-NRCS). Soil Survey Geographic (SSURGO) Database (2008). Available online at http://soils.usda.gov/survey/geography/ssurgo/ (verified on May 25, 2009).
31. Van Meirvenne M., and Hofman G. Spatial variability of soil nitrate nitrogen after potatoes and its change during winter. Plant Soil. 120 1 (1989) 103-110
32. Webster R., and Oliver M.A. Geostatistics for Environmental Scientists (2001), John Wiley & Sons Ltd., Chichester