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Traditionally, potential evaluation methods for farmland consolidation havedepended mainly on the experts' experiences, statistical computations orsubjective adjustments. Some biases usually exist in the results. Thus,computer-aided technology has become essential. In this study, anintelligent evaluation system based on a fuzzy decision tree wasestablished, and this system can deal with numerical data, discrete data andsymbolic data. When the original land data are input, the level of potentialof the agricultural land for development will be output by this new model.The provision of objective proof for decision-making by authorities in ruralmanagement is helpful. Agricultural land data characteristically compriselarge volumes, complex varieties and more indexes. In land consolidation, itis very important to construct an effective index system. A group of indexesneed to be selected for land consolidation. In this article, a fuzzy measure was adopted to accomplish the selection of specific features. Afuzzy integral based on a fuzzy measure is a type of fusion tool. Theoptimal solution with the fewest non-zero elements was obtained for the fuzzy measure by solving a fuzzy integral. This algorithm provides a quick andoptimal way to identify the land-index system when preparing to conduct landconsolidation. This new research was applied to Shunde's "Three Old"consolidation project which provides the data. Our estimation system wascompared with a conventional evaluation system that is still accepted by thepublic. Our results prove to be consistent, and the new model is moreautomatic and intelligent. The results of this estimation system aresignificant for informing decision-making in land consolidation

A fuzzy intelligent system for land consolidation – a case study in Shunde, China