Annals of Operations Research

, Volume 219, Issue 1, pp 203–229 | Cite as

Application of Decision Theory methods for a soil classification in the Community of Madrid (Spain)

  • José M. Antón
  • Ana M. Tarquis
  • Juan B. Grau
  • Elena Sánchez
  • Antonio Saa
  • Mari-Cruz Díaz
Article

Abstract

A land classification method was designed for the Community of Madrid (CM), which has lands suitable for either agriculture use or natural spaces. The process started from an extensive previous CM study that contains sets of land attributes with data for 122 types and a minimum-requirements method providing a land quality classification (SQ) for each land. Borrowing some tools from Operations Research (OR) and from Decision Science, that SQ has been complemented by an additive valuation method that involves a more restricted set of 13 representative attributes analysed using Attribute Valuation Functions to obtain a quality index, QI, and by an original composite method that uses a fuzzy set procedure to obtain a combined quality index, CQI, that contains relevant information from both the SQ and the QI methods.

Keywords

Pedology Soil science Qualification Classification Soil quality Land capability Valuation function Additive valuation Threshold requirements Fuzzy set 

Abbreviations

ADV

attribute data value, corresponding to a j-attribute for an i-land, e.g. in Sect. 3.1.

AQI

attribute quality index, value falling in a nominal range (0,1), obtained using an AVF.

AVF

attribute valuation function, to obtain an AQI from a j-attribute data ADV for an i-land.

CEC

Cation Exchange Capability, used in “CEC attribute value” for an i-land.

CM

is used in this paper for Comunidad de Madrid.

CM study

(Gallardo et al. 2005), survey for CM that is the primary source for the methods in the paper.

CQI

combined soil quality index, giving a “CQI value” for an i-land in nominal range (0, 1); used to obtain a “CQI qualification”, also in “CQI method” to obtain “CQI values”.

CP

Compromise Programming.

DS

Decision Science.

EC

Electric conductivity, used in “EC attribute value” for an i-land.

ESP

Exchange Sodium Percentage, used in “ESP attribute value” for an i-soil of an i-land.

ETS

Escuela Técnica Superior in Spain, Technical School for Engineers, Superior is “of upper degree”; also its building and organisation or its entity with actual evolving organisation (e.g., with Bolonia plans).

ETSIA

School of Agronomical Engineers of Madrid, from Escuela Técnica Superior de Ingenieros Agrónomos.

FAO

Food and Agriculture Organisation of the United Nations.

LI

limiting index, as δi,k,j, defined in Sect. 4 by formula (4) to be used with formula (5).

MS EXCEL

Microsoft EXCEL software.

MX

missing index, Sect. 3.1, Sect. 4, indicating missing data values.

OR

Operations Research.

QI

quality index, defined in this paper getting a “QI value” QI in nominal range (0,1) for an i-soil with the related “QI method”, to obtain a “QI qualification”.

SCR

Soil Sealing and Crusting Risk, attribute for SQ classification, Sect. 2.2, the Appendix.

SQ

soil quality, refers mostly to the “SQ classification” in “SQ classes”, with SQ index being (I to IX) or (1 to 9), appears in the “SQ method” to obtain them, in the “SQ authors” of it, and also in “SQ criteria or attributes” corresponding to data for that method.

SAR

Sodium Absorption Rate, used in “SAR attribute” value for an i-soil of an i-land.

SS

Soil Science.

UPM

Universidad Politécnica de Madrid.

USDA

United States Department of Agriculture.

USLE

Universal Soil Loss Equation, used in “USLE-C attribute” (elsewhere found in an USLE/RUSLE acronym).

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References

  1. Aguilar, J., & Ortíz, R. (1992). Metodología de capacidad de uso agrícola de los suelos. In Sociedad Española de la Ciencia del Suelo, III Congreso Nacional de la Ciencia del Suelo, Pamplona (pp. 281–286). Google Scholar
  2. Allan, D. L. et al. (1995). Soil quality: a conceptual definition. Soil Science Society of America Agronomy News, June 1995, p. 7. Google Scholar
  3. Anton, J. M., Grau, J. B., & Sánchez, E. M. (2007a). Compromise programming calibration for financial analysis of firms of a common sector of business, case study for a set of Spanish banks in 1995. Applied Financial Economics 17, 445–461. CrossRefGoogle Scholar
  4. Anton, J. M., Grau, J. B., Tarquis, A. M., Saa, A., & Sánchez, E. M. (2007b). Application of Decision Theory methods for a Community of Madrid soil classification case, extended abstract for ORAFM stream/session in EURO2007 (Prague, July 8–11) accepted and printed in Journal of Agricultural Science. Google Scholar
  5. Azevedo, A. L., & Cardoso, J. C. (1962). Soil classification in Portugal and its application in agricultural research. Trans. Comm. IV and V. Int. Soc. Soil. Sci. New Zealand, pp. 473–479. Google Scholar
  6. Belacel, N. (2000). Multicriteria assignment method PROAFTN: Methodology and medical applications. European Journal of Operational Research, 125, 175–183. CrossRefGoogle Scholar
  7. Chang, N. B., Yeh, S. C., & Wu, G. C. (1999). Stability analysis of grey compromise programming and its application to watershed land-use planning. International Journal of Systems Science, 30(6), 571–589. CrossRefGoogle Scholar
  8. De Pauw, E., & Zoebisch, M. A. (2002). Greenhouse effect and soil degradation. In R. Lal (Ed.), Encyclopedia of soil science (pp. 307–310). New York: Marcel Dekker. Google Scholar
  9. Dent, D., & Young, A. (1981). Soil survey and land evaluation. London: Allen & Unwin. Google Scholar
  10. Driessen, P. M., & Konijn, N. T. (1992). Land-use systems analysis. Wageningen Agricultural University, Department of Soil Science & Geology: Malang: INRES, 230p. Google Scholar
  11. FAO (1976). A framework for land evaluation. Soils Bulletin No 32. Roma: FAO. Google Scholar
  12. Figueira, J., de Smet, I., & Brans, J.-P. (2004a). MCDA methods for sorting and clustering problems: PROMETHEE TRI and PROMETHEE CLUSTER. Université Libre de Bruxelles. http://www.ulb.ac.be/polytech/smg/inexpublications.htm, Service de Mathématiques de la Gestion, #2004/02.
  13. Figueira, J., Tervonen, T., Almeida-Dias, J., Lahdelma, R., & Salmiken, P. (2004b). SMAA-TRI: a parameter stability analysis method for ELECTRE TRI. In NATO advanced research workshop, 20–24 April 2004, Thessaloniki, Greece. Google Scholar
  14. Figueira, J., Greco, S., & Ehrgott, M. (Eds.) (2005). Multiple criteria decision analysis, state of the art surveys. Operations research & management in science. Springer International Series. Google Scholar
  15. Gallardo, J., Almorox, J., & Hontoria, C. (2002a). Clasificación de la capacidad agrológica de las tierras. 46p. Ed. ETSI Agrónomos, Madrid. Google Scholar
  16. Gallardo, J., Hontoria, C., Almorox, J., & Saa, A. (2002b). Capacidad Agrológica de las Tierras. Monografía de ETSI Agrónomos, pp. 55, Madrid. Google Scholar
  17. Gallardo, J., Saa, A., Hontoria, C., & Almorox, J. (2005). Mapa Agrológico: Capacidad Agrológica de las tierras de la Comunidad de Madrid. Ed. D.G. de Urbanismo y Planificación Regional, C.M., pp. 98. Google Scholar
  18. Gregorich, E. G. (2002). Soil quality. In R. Lal (Ed.), Encyclopedia of soil science (pp. 1058–1061). New York: Dekker. Google Scholar
  19. Grau, J. B., Antón, J. M., Saa, A., Díaz, M. C., & Tarquis, A. M. (2006). Mathematical decision theory applied to soil quality. Poster, 18th world congress of soil science, July 9–15, 2006, Philadelphia, Pennsylvania, USA. Google Scholar
  20. Greco, S., Matarazzo, B., & Slowinski, R. (1999). The use of rough sets and fuzzy sets in MCDM. In T. Gal, T. Hanne, & T. Stewart (Eds.), Advances in multiple criteria decision-making (pp. 14.1–14.59). Dordrecht: Kluwer Academic. Google Scholar
  21. Greco, S., Matarazzo, B., & Slowinski, R. (2001). Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129, 1–47. CrossRefGoogle Scholar
  22. Gunn, R. H., Beattie, J. A., Reid, R. E., & Graaff, R. H. M. (Eds.) (1988). Australian soil and land survey handbook: guidelines for conducting surveys. Melbourne: Inkata Press. Google Scholar
  23. Klingebiel, A. A., & Montgomery, P. H. (1961). USDA agricultural handbook: Vol. 210. Land capability classification. Washington: US Government Printing Office, pp. 21. Google Scholar
  24. Koo, B. K., & O’Connell, P. E. (2005). An integrated modelling and multi-criteria analysis approach to managing nitrate diffuse pollution: framework and methodology. Science of the Total Environment, 359(1–3), 1–16. Google Scholar
  25. Krcmar, E., Van Kooten, G. C., & Vertinsky, I. (2005). Managing forest and marginal agricultural land for multiple tradeoffs: compromise on economic, carbon and structural diversity objectives. Ecological Modelling, 185(2–4), 451–468. CrossRefGoogle Scholar
  26. Ministerio de Agricultura (1974). Caracterización de la Capacidad Agrológica de los suelos de España. Metodología y Normas. Madrid: Ministerio de Agricultura. Google Scholar
  27. Moraes, M. H., Gomar, P. E., Benez, S. H., & Barilli, J. (2002). Effects of long-term management systems on soil quality. In 12th international Soil Conservation Organization (ISCO) conference, May 26–31, Beijing (Vol. II, pp. 187–192). Google Scholar
  28. Ocio, J. A., Jiménez Ballesta, R., & Guerra, A. (1987). Aproximación a la evaluación paramétrica de suelos para distintos usos en Rioja alavesa. Comunicaciones Tomo II: Geología Ambiental y Ordenación del Territorio. III Reunión Nacional Valencia. Google Scholar
  29. Riquier, J., Bramao, D. L., & Cornet, J. P. (1970). A new system of soil appraisal in terms of actual and potential productivity. FAO Soil Resources, Development and Conservation Service, Land and Water Development Division. FAO Rome, pp. 38. Google Scholar
  30. Romero, C. (1993). Teoría de la decisión multicriterio. Madrid: Alianza Universidad Textos. Google Scholar
  31. Roy, B., & Bouyssou, D. (1993). Aide Multicritère à la Décision: Méthodes et Cas. Economica. Paris. Google Scholar
  32. Roy, B., & Figueira, J. (2002). Determining the weights of criteria in the ELECTRE type methods with a revised Simo’s procedure. European Journal of Operational Research, 139, 317–326. CrossRefGoogle Scholar
  33. Sánchez, J., Rubio, J. L., Martínez, V., & Antolín, C. (1984). Metodología de capacidad de uso de los suelos para la Cuenca Mediterránea. In I Congreso Nacional de la Ciencia del Suelo, Madrid (Vol. II, pp. 837–848). Google Scholar
  34. Schipper, L. A., & Sparling, G. P. (2000). Performance of soil condition indicators across taxonomic groups and land uses. Soil Science Society of America Journal, 64, 300–311. CrossRefGoogle Scholar
  35. Strager, M. P., & Rosenberger, R. S. (2007). Aggregating high-priority landscape areas to the parcel level: an easement implementation tool. Journal of Environmental Management, 82(2), 290–298. CrossRefGoogle Scholar
  36. Weintraub, A., Romero, C., Bjørndal, T., Epstein, R., & Miranda, J. (2007). Handbook of operations research in natural resources. New York: Springer. Google Scholar
  37. Yu, P. L. (1973). A class of solutions for group decisions problems. Management Science, 19, 936–946. CrossRefGoogle Scholar
  38. Zeleny, M. (1973). In J. L. Cochrane & M. Zeleny (Eds.), Compromise programming in multiple criteria decision making (pp. 262–301). Berlin: Springer. Google Scholar
  39. Zornoza, R., Mataix-Solera, J., Guerrero, C., Arcenegui, V., Mataix-Beneyto, J., Morales, J., & Mayoral, A. M. (2006). Modelling an index for soil quality evaluation based on natural forest soils under Mediterranean conditions. Geophysical Research Abstracts, 8, 03284. Google Scholar
  40. Zopounidis, C., & Doumpos, M. (2002). Multicriteria classification and sorting methods: a literature review. European Journal of Operational Research, 138(2), 229–246. CrossRefGoogle Scholar
  41. Zopounidis, C., & Doumpos, M. (2004). Multicriteria decision aid in classification problems. EWG-MCDA Newsletter, Series 3, No. 10, Fall 2004. Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • José M. Antón
    • 1
  • Ana M. Tarquis
    • 1
  • Juan B. Grau
    • 1
  • Elena Sánchez
    • 1
  • Antonio Saa
    • 2
  • Mari-Cruz Díaz
    • 2
  1. 1.Dto. Matemática AplicadaE.T.S. de Ing. Agrónomos, U.P.M.MadridSpain
  2. 2.Dto. EdafologíaE.T.S. de Ing. Agrónomos, U.P.M.MadridSpain

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