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Title: Evaluation of Resources of Agricultural Lands Using Fuzzy Indicators

Author
item Torbert, Henry - Allen
item YAKUSHEV, V - Agro Research Institute Of Russia
item KRUEGER, E - Agro Research Institute Of Russia
item KURTENER, D - Agro Research Institute Of Russia

Submitted to: International Soil Tillage Research Organization Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 6/16/2009
Publication Date: 6/16/2009
Citation: Torbert III, H.A., Yakushev, V., Krueger, E., Kurtener, D. 2009. Evaluation of Resources of Agricultural Lands Using Fuzzy Indicators. In: Sustainable Agriculture, Proceedings of 18th International Conference of the International Soil Tillage Research Organization, June 15-19, 2009, Izmir, Turkey. 2009 CDROM.

Interpretive Summary: With ever increasing demands on agriculture, it is essential that we be able to adequately evaluate agriculture land resources. 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 for this procedure 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.