A proper characterization of land-use types is critical for constructing generalization constraints to guide and control landuse data generalization. This paper focused on identification and utilization of their importance based upon land-use distributions and application themes. First, this importance was identified using a three-step method that links a diversity index, a multiple attribute decision model and a spatial association analysis. Second, with the importance, a mathematical function was designed to determine minimum area thresholds of land-use polygons as an example of generalization constraints. Third, the importance was used to assist in the selection of generalization operators and evaluation of generalization outcomes. Fourth, a land-use dataset at 1:10 000, describing the land use of a typical rural area in Hubei province of China, was generalized towards a 1:50 000 dataset to verify the effects of the presented method and function. Three additional tests were implemented to analyze the sensitivity of the importance of land-use types on setting the minimum area threshold and generalization operations. The outcome showed that the proposed methods and functions make land-use data generalization more adaptable for in-use datasets and applications.