Land-use data generalization is one of the basic operations for deriving multi-scale data from a comprehensive land-use database. Acquiring data characteristics and converting them into generalization rules used to implement data generalization is an effective way to improve the objectivity and validity for land-use data generalization. This paper focuses on the extraction and application of region-dependent rules for land-use data generalization. First

the objectives and hierarchy of the rules are clarified. Then

spatial association analysis and landscape indices are employed to set the importance ranks

minimum area thresholds and spatial distribution pattern of each land-use class. Finally

a case study was undertaken to show the application of these rules using 110 000 land-use data around Jiufeng county of Hubei

China.