The methods of spatial data aggregation based on majority and random rules were used in this study to reveal the scaling effects on landscape pattern in a classified TM imagery with 8 land cover types. For the majority rule-based aggregations, the proportion of most common cover types increased slowly, while that of less common cover types decreased rapidly with increasing grain. For random rule-based aggregation, each cover remained its original area on the aggregated maps. The largest patch sizes of shrub decreased, and those of the others increased in the majority rule-based aggregations with increasing scales. For random rule, the largest patch size of water (smallest cover type) decreased, but that of the others increased. The smallest patch size of each cover type was equal to the square of grain sizes. The average patch size of each cover type increased with increasing scales. However, the average patch size of dominant cover types increased rapidly in majority rule-based aggregations, while that of less common cover types increased rapidly in random rule-based aggregation. The patch count of each cover types decreased substantially with increasing grain. Random rule-based aggregation made landscape more fragmented and remained more patches. The diversity decreased in majority rule-based aggregation, and maintained its original value in random rule-based aggregation with increasing scales. Aggregation indices decreased with increasing map and measurement resolution, and the landscape became more aggregated in majority rule-based aggregation. However, under fixed measurement resolution (e.g., 30 m), aggregation indices increased and cover types were more clustered with increasing resolution. Moran's I decreased rapidly with increasing measurement and map resolution, and each cover type tended to be arranged randomly and independently in space. However, under fixed measurement resolution (e.g., 30 m), Moran's I increased and cover types were more clustered on aggregated maps than on original map with increasing map resolution.