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Precision crop management is by definition a multi-objective decision-making process that must incorporate a diversity of data, opinion, preference and objective. This paper details an approach to decision making that allows users to express individual or corporate values and preferences; highlights the degree of imprecision associated with each input; highlights the degree of imprecision associated with each alternative; facilitates structuring of the decision process; reduces several levels of complex information into a single chart; allows examination of trade-off between alternatives and interests; and forces examination of inter-relationships between interest. The addition of using remote sensing data provides an efficient method to describe spatial variability in terms that can be related to a crop model, making the decision- making approach feasible for precision farming applications. The crop model provides information that can be used by the decision model, and the remote sensing data is used to fine tune the calibration of the crop model, maximizing the accuracy of its results.