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Recently, land use and land cover change have received increased attention, and an approach is required that can assess agricultural land use intensity on a general basis. This study demonstrated the usefulness of a tool for characterizing and assessing agricultural land use intensity in Beijing mountainous region. An emergy analysis and principal component analysis (PCA) were adopted to obtain agricultural input and output intensity data. Correlation and regression analyses were used to study the relationship among land capability, agricultural input, output intensity, and agricultural system sustainability. Ultimately, the agricultural land use intensity types in the Beijing mountainous region were identified through a cluster analysis. The results produced five indices of agricultural input intensity and five indices of output intensity. Non-renewable energy was the overwhelming input, and grain, meat, eggs, and vegetables were the major outputs of the agricultural system. The results also showed that there was better natural land quality, higher input intensity, greater output intensity, and lower agricultural system sustainability. Eight types of agricultural intensity were classified and assessed, and they may be used to evaluate and monitor sustainable land use and provide baseline measurements of land use intensity for land use analyses and change detection

Characterizing and Assessing the Agricultural Land Use Intensity of the Beijing Mountainous Region