An approach for delineating homogeneous within-field zones using proximal sensing and multivariate geostatistics

Agricultural Water Management

Volumn 147, Issue , 2015, Pages 144-153

  Landrum, Carla ^a   Castrignanò, Annamaria ^b   Mueller, Tom ^a   Zourarakis, Demetrio ^c   Zhu, Junfeng ^a   De Benedetto, Daniela ^b  

^a UNIVERSITY OF KENTUCKY   (United States)

^b ISTITUTO NAZIONALE DELLA NUTRIZIONE   (Italy)

^c Remote Sensing and GIS Analyst Kentucky   (United States)

Author keywords

Apparent electrical conductivity; Data fusion; LiDAR; Multicollocated factorial cokriging; Soil moisture variation

Indexed keywords

DATA FUSION; ELECTRIC CONDUCTIVITY; LANDFORMS; MOISTURE; MOISTURE METERS; OPTICAL RADAR; PLANTS (BOTANY); SOIL MOISTURE; SOILS;

APPARENT ELECTRICAL CONDUCTIVITY; CO-KRIGING; EXPLORATORY STATISTICS; LINEAR MODEL OF COREGIONALIZATION; MOISTURE VARIATION; MULTIVARIATE GEOSTATISTICS; SOIL MOISTURE DISTRIBUTION; SOIL PHYSICAL AND CHEMICAL PROPERTIES;

SOIL SURVEYS;

ELECTRICAL CONDUCTIVITY; GEOSTATISTICS; HOMOGENEOUS MEDIUM; KARST; LIDAR; MULTIVARIATE ANALYSIS; SOIL MOISTURE; SOIL ORGANIC MATTER; SOIL TEXTURE; WATER MANAGEMENT;

KENTUCKY; UNITED STATES;

EID: 84908371191     PISSN: 03783774     EISSN: 18732283     Source Type: Journal    
DOI: 10.1016/j.agwat.2014.07.013     Document Type: Article

References (42)

1. Adamchuk V.I., 'Hummel J.W., Morgan M.T., Upadhyaya S.K. On-the-go soil sensors for precision agriculture. Comput. Electron. Agric. 2004, 44:71-91.
2. Beckett P.H.T., Burrough P.A. The relation between cost and utility in soil survey: IV. Comparison of the utilities of soil maps produced by different survey procedures, and to a different scales. J. Soil Sci. 1971, 22:460-480.
3. Benton Jones J. Soil Analysis Handbook of Reference Methods 2000, Soil and Plant Analysis Council Inc. CRC Press, Boca Raton, FL.
4. Carroll S.S., Cressie N.A. Comparison of geostatistical methodologies used to estimate snow water equivalent. Water Resour. Bull. 1996, 32(2):267-278.
5. Castrignanò A., Wong M.T.F., Stelluti M., De Benedetto D., Sollitto D. Use of EMI, gamma-ray emission and GPS height as multi-sensor data for soil characterisation. Geoderma 2012, 175-176:78-89.
6. Castrignanò A. Introduction to Spatial Data Processing 2011, Aracne (Ed.).
7. Castrignanò A., Costantini E.A.C., Barbetti R., Sollitto D. Accounting for extensive topographic and pedologic secondary information to improve soil mapping. Catena 2009, 77:28-38.
8. Castrignanò A., Giugliarini L., Risaliti R., Martinelli N. Study of spatial relationships among some soil physio-chemical properties of a field in Central Italy using multivariate geostatistics. Geoderma 2000, 97(1-2):39-60.
9. Chilés J.P., Delfiner P. Geostatistics: Modeling Spatial Uncertainty 1999, John Wiley & Sons, Inc., New York, NY.
10. Corwin D.L., Lesch S.M. Application of soil electrical conductivity to precision agriculture: theory, principles, and guidelines. Agron. J. 2003, 95:455-471.
11. De Benedetto D., Castrignanò A., Rinaldi M., Ruggieri S., Santoro F., Figorito B., Gualano S., Diacono M., Tamborrino R. An approach for delineating homogeneous zones by using multi-sensor data. Geoderma 2013, 199:117-127.
12. De Benedetto D., Castrignanò A., Sollitto D., Modugno F., Buttafuoco G., Lo Papa G. Integrating geophysical and geostatistical techniques to map the spatial variation of clay. Geoderma 2012, 171-172:53-63.
13. De Benedetto D., Castrignanò A., Sollitto D., Modugno F. Spatial relationship between clay content and geophysical data. Clay Miner. 2011, 45(2):197-207.
14. ESRI ArcMap 10. 0 2012, Environmental Systems Research Institute, Badlands, CA, USA.
15. Evans R.G., Han S., Kroeger M.W., Schneider S.M. Precision centre pivot irrigation for efficient use of water and nitrogen. Proceedings of the Third International Conference on Precision Agriculture, ASA/CSSA/SSSA 1996, 75-84.
16. FAO Save and Grow. A Policymaker's Guide to the Sustainable Intensification of Smallholder Crop Production 2011, Food and Agriculture Organization of the United Nations (FAO), Rome.
17. Fridgen J.J., Kitchen N.R., Sudduth K.A., Drummond S.T., Wiebold W.J., Fraisse C.W. Management Zone Analyst (MZA): Software for subfield management zone delineation. Agron. J. 2004, 96:100-108.
18. Geovariances, Ecole Des Mines De Paris Isatis Technical Ref., release 13.1 2013, Geovariances, Avon Cedex, France.
19. Gomez-Plaza A., Alvarez-Rogel J., Albaladejo J., Castillo V. Spatial patterns and temporal stability of soil moisture across a range of scales in a semi-arid environment. Hydrol. Processes 2000, 14:1261-1277.
20. Goovaerts P. Geostatistics for Natural Resource Evaluation 1997, Oxford University Press, Athens.
21. Grayson R., Western A., Chiew F., Bloschl G. Preferred states in spatial soil moisture patterns: local and nonlocal controls. Water Resour. Res. 1997, 33(12):2897-2908.
22. Hartsock N.J. In situ soil electrical conductivity variability in several Kentucky agricultural fields. Plant and soil sciences. Master's Thesis 2001, University of Kentucky, Lexington.
23. Heuvelink G.B.M. Identification of field attribute error under different models of spatial variation. Int. J. GIS 1996, 10:921-935.
24. Islam M.M., Saey T., Meerschman E., De Smedt P., Meeuws F., Van De Vijver E., Van Meirvenne M. Delineating water management zones in a paddy rice field using a Floating Soil Sensing System. Agricult. Water Manage. 2011, 102(1):8-12.
25. Journel A., Huijbregts C. Mining Geostatistics 1978, 600. Academic Press, London.
26. Kerry R., Oliver M.A., Frogbrook Z.L. Sampling in Precision Agriculture. Geostatistical Applications for Precision Agriculture 2010, 35-63.
27. Lajaunie C., Behaxeteguy J.P. Elaboration d'un programme d'ajustement semi-automatique d'un modele de coregionalisation e Theorie. Technical Report N21/89/G 1989, 6. ENSMP, Paris.
28. Khosla R., Shaver T. Zoning in on Nitrogen Needs 2001, 21:24-26. Colorado State University Agronomy Newsletter.
29. Ma R., McBratney A., Whelan B., Minansy B., Short M. Comparing temperature correction models for soil electrical conductivity measurement. Precis. Agric. 2011, 12:55-66.
30. Marchant B.P., Lark R.M. Sampling in precision agriculture, optimal designs from uncertain models. Geostatistical Applications for Precision Agriculture 2010, 65-87. Springer, The Netherlands. M.A. Oliver (Ed.).
31. Matheron G. The intrinsic random functions and their applications. Adv. Appl. Probab. 1973, 5:239-465.
32. Nguyen H., Cressie N., Braverman A. Spatial statistical data fusion for remote sensing applications. J. Amer. Statist. Assoc. 2012, 107(499):1004-1018.
33. Rivoirard J. Which models for collocated cokriging?. Math. Geol. 2001, 33(2):117-131.
34. Saxton K.E.a.W.J.R. Soil water characteristic estimates by texture and organic matter for hydrologic solutions. Soil Sci. Soc. Am. J. 2006, 70:1569-1578.
35. Stafford J.V. Essential technology for precision agriculture. Proceedings of the Third International Conference on Precision Agriculture 1996, 595-604.
36. Stafford J.V., Lark R.M., Bolam H.C. Using yield maps to regionalize fields into potential management units. Proceedings of the Fourth International Conference on Precision Agriculture ASA/CSSA/SSSA 1998, 225-237. P.C. Robert, R.H. Rust, W.E. Larson (Eds.).
37. Taylor J., Short M., McBratney A.B., Wilson J. Comparison of the ability of multiple soil sensors to predict soil properties in a Scottish potato production system. Proceedings of First Global Workshop on High Resolution Digital Soil Sensing & Mapping 2008.
38. USDA-NRCS Official Soil Series Classification Database 2013, USDA-NRCS, www.websoilsurvey.nrcs.usda.gov/
39. Vachaud G., De Silans A., Balabanis P., Vauclin M. Temporal stability of spatially measured soil water probability density function. Soil Sci. Soc. Am. J. 1985, 49:822-828.
40. van Groenigen J.W., Siderius W., Stein A. Constrained optimisation of soil sampling for minimization of the kriging variance. Geoderma 1999, 87:239-259.
41. Wackernagel H. Multivariate Geostatistics: An Introduction with Applications 2003, Springer-Verlag, Berlin.
42. Zhang N., Wang M., Wang N. Precision agriculture-a worldwide overview. Comput. Electron. Agric. 2002, 36:113-132.