Abstract: A field experiment was conducted in the Experiment Station Farm of South China Agricultural University located in Guangzhou China to investigate the effect of sugarcane planting patterns (sugarcane monoculture, sugarcane-sweet corn 1∶1 intercropping, and sugarcanesweet corn 2∶1 intercropping) and different N input levels (300,  525 kg·hm^-2) on yield, total biomass dynamic, quality and economic benefit of sugarcane. Results showed that the economic benefit of sugarcanesweet corn intercropping with the low N level was 52.67% to 20.59% (sugarcane-sweet corn 1∶1 to 2∶1 intercropping) higher than that of sugarcane monoculture, and the land equivalent ratio (LER) of which was higher than 1. The LER of sugarcane-sweet corn 1∶1 intercropping system was 31.5% higher than that of sugarcane-sweet corn 2∶1 intercropping system. Meanwhile, the economic benefit and the LER of sugarcane-sweet corn 1∶1 intercropping system with the high N level were 26.25% and 36.00% higher than that of sugarcane monoculture respectively, but the sugarcane-sweet corn 2∶1 intercropping system with the high N level had no advantages compared with the sugarcane monoculture. In the sugarcanesweet corn intercropping system, the yield of intercropped sugarcane was 9.72%-33.17% lower than that of monoculture because the eigenvectors such as maximum growth rate (v_m), theoretical maximum (w_m) and the fastest growth day (t_m) of the dynamic accumulation model of intercropped sugarcane were more uncoordinated than those of monoculture. However, the yield of intercropped sweet corn was 14.10%-24.43% higher than that of monoculture. Compared with sugarcane monoculture, sugarcane-sweet corn intercropping patterns had no significant effect on sugarcane quality. Therefore, it is feasible to apply sugarcane-sweet corn intercropping to realize high quality and high efficiency planting of sugarcane, and the sugarcane-sweet corn 1∶1 intercropping is the optimum intercropping pattern.

Key words: SPOT5., object-based method, forest inventory parameter, decision tree, aboveground carbon storage