Although correlations between soil respiration (R_s) and environmental factors in different ecosystems have been extensively investigated, results based on long-term experiments are limited. In this study, we analyzed the correlations between R_s and soil temperature (T_s), moisture (θ), the normalized difference vegetation index (NDVI), and soil organic matter (SOM) based on an 11-year field campaign in abandoned farmland (HD) and bare land (LD) areas with a Cambisol soil type in the eastern Loess Plateau of China. The results showed that the mean annual R_s and annual temperature sensitivity (Q₁₀) values in HD were significantly larger than those in LD during the measurement period. R_s and the annual contribution ratio (R_ratio) of root respiration (R_r) to R_s in HD increased significantly with vegetation recovery years. On the annual scale, R_s was controlled primarily by T_s at both sites. However, in the summer months, R_s was controlled by θ rather than T_s. A two-variable model, including T_s and θ, could more accurately predict the temporal variations in R_s at the annual and seasonal time scales than a single-variable model, and the explanatory power of the equations in HD was significantly larger than that in LD. On the interannual scale, variations in the annual R_s and R_r showed significant positive correlations with the annual θ and NDVI and SOM, and negative correlations with T_s in HD. Moreover, the annual Q₁₀ was significantly positively related to θ in HD. In LD, the only significant relationship was between the annual Q₁₀ and the annual θ. All differences between HD and LD in R_s, T_s, and θ and their correlations were attributed to differences in vegetation. Our findings highlight the importance of long-term observations for the accurate estimation of CO₂ efflux in semiarid regions and the impact of vegetation changes on soil respiration.