Abstract: Since the change of regional land use pattern influences agricultural system with the urban expansion and population growth, an approach to quantify agricultural land use intensity on a common basis is very necessary. Taking Beijing suburban districts and counties as a case, agricultural land use intensity through principal component analysis (PCA) and cluster analysis was investigated to identify its characteristics and types with translating each form of socio-economic data into its solar emergy by way of a conversion factor (transformity). In the study areas four indices of agricultural input intensity and six indices of output intensity were identified, then those components were combined to input intensity index and output intensity index, respectively. Six types of agricultural intensity were identified through K-means cluster analysis using intensity indices, and 34% of the experimental towns belong to low input and moderate output intensity, while 27% of the experimental towns belong to low input and low output intensity. The results showed PCA could provide available indices of land use intensity for an overall assessment of regional agricultural land use intensity, and the emergy method could make the results more solubility.