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ARS Home » Southeast Area » Auburn, Alabama » Soil Dynamics Research » Research » Publications at this Location » Publication #253987
Title: Development and application of fuzzy indicator for assessment of agricultural land resources

Author
item Torbert, Henry - Allen
item YAKUSHEV, V - Russian Academy Of Sciences
item KRUEGER, E - Russian Academy Of Sciences
item KURTENER, D - Russian Academy Of Sciences

Submitted to: Book Chapter
Publication Type: Book / Chapter
Publication Acceptance Date: 7/9/2010
Publication Date: 7/9/2010
Citation: Torbert III, H.A., Yakushev, V., Krueger, E., Kurtener, D. 2010. Development and application of fuzzy indicator for assessment of agricultural land resources. In: Kurtener, D., Yakushev, V.P., Torbert, H.A., Prior, S.A., and Krueger, E., editors. Applications of Soft Computing in Agricultural Field Experimentations. St. Petersburg, Russia: Agrophysical Research Institute. p. 103-117.

Interpretive Summary: With ever increasing demands on agriculture, it is essential that we be able to adequately evaluate agriculture land resources. Recently, efforts have been undertaken to develop methods and tools for the purpose of evaluating agricultural land resources. However, to be successful, assessments need to incorporate the state of the art knowledge in agronomy, soil science, and economics into a user-friendly, decision support tool. Also, it is well known that the process of assessment land resources is full of uncertainty. Uncertainty is inherent in this process, which involve data and model uncertainty that range from measurement error, to inherent variability, to instability, to conceptual ambiguity, to over-abstraction, or to simple ignorance of important factors. This manuscript examines the evaluation of land resources as a fuzzy modeling task. Data collected from a precision agriculture study in central Texas, USA was utilized for the assessment of land resources, and a model of fuzzy indicators and procedures for computer simulations were developed. The theoretical considerations are illustrated within this example.

Technical Abstract: With ever increasing demands on agriculture, it is essential that we be able to adequately evaluate agriculture land resources. Recently, efforts have been undertaken to develop methods and tools for the purpose of evaluating agricultural land resources. However, to be successful, assessments need to incorporate the state of the art knowledge in agronomy, soil science, and economics into a user-friendly, decision support tool. Also, it is well known that the process of assessment land resources is full of uncertainty. Uncertainty is inherent in this process, which involve data and model uncertainty that range from measurement error, to inherent variability, to instability, to conceptual ambiguity, to over-abstraction, or to simple ignorance of important factors. This manuscript examines the evaluation of land resources as a fuzzy modeling task. Data collected from a precision agriculture study in central Texas, USA was utilized for the assessment of land resources, and a model of fuzzy indicators and procedures for computer simulations were developed. The theoretical considerations are illustrated within this example.