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Journal of Environmental Quality Abstract - Short Communications

Mathematical Decision Theory Applied to Land Capability: A Case Study in the Community of Madrid


This article in JEQ

  1. Vol. 43 No. 2, p. 763-774
    Received: Mar 21, 2012
    Published: June 23, 2014

    * Corresponding author(s): antonio.saa@upm.es
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  1. J. M. Antóna,
  2. A. Saa-Requejo *bc,
  3. J. B. Graua,
  4. J. Gallardob,
  5. M.C. Díazbc,
  6. Diego Andinad,
  7. M. E. Sancheza and
  8. A. M. Tarquisac
  1. a Dep. de Matemática Aplicada, E.T.S. Ing. Agrónomos, UPM, Ciudad Universitaria, 28040 Madrid, Spain
    b Dep. de Edafología y Climatología, E.T.S. Ing. Agrónomos, UPM, Ciudad Universitaria, 28040 Madrid, Spain
    c CEIGRAM, E.T.S. Ing. Agrónomos, UPM, Ciudad Universitaria, 28040 Madrid, Spain
    d Dep. de Señales, Sistemas y Radiocomunicaciones, E.T.S. de Ing. de Telecomunicaciones, UPM, Ciudad Universitaria, 28040 Madrid, Spain


In land evaluation science, a standard data set is obtained for each land unit to determine the land capability class for various uses, such as different farming systems, forestry, or the conservation or suitability of a specific crop. In this study, we used mathematical decision theory (MDT) methods to address this task. Mathematical decision theory has been used in areas such as management, finance, industrial design, rural development, the environment, and projects for future welfare to study quality and aptness problems using several criteria. We also review MDT applications in soil science and discuss the suitability of MDT methods for dealing simultaneously with a number of problems. The aim of the work was to show how MDT can be used to obtain a valid land quality index and to compare this with a traditional land capability method. Therefore, an additive classification method was applied to obtain a land quality index for 122 land units that were compiled for a case study of the Community of Madrid, Spain, and the results were compared with a previously assigned land capability class using traditional methods based on the minimum requirements for land attributes.

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Copyright © 2014. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.