Abstract: This study systematically analyzed the spatial distribution of the influencing factors of farmland soil organic carbon (SOC) in the Poyang Lake region by using the geographically weighted regression (GWR) model, and combined kriging interpolation algorithm to produce SOC map. The GWR Kriging (GWRK) and kriging (RK) methods were compared to identify the difference in predicting the SOC reserves. The results showed that: 1) The selected environmental influencing factor was relevant with SOC (P<0.01) according to Pearson correlation analysis; 2) There was a positive correlation between SOC and aspect, annual average temperature, and annual average precipitation, while a negative correlation was observed between SOC and gradient, vegetation coverage; 3) The values of SOC content ranged from 6.35 to 31.93 g kg-1 using the method of GWRK and approached to the measured values of sampling points. The values of SOC content ranged from 7.41 to 2.76 g·kg^-1 using the method of RK, and the overall spatial distribution characteristics were similar to the results of GWRK; however, the predicting results of RK were relatively smooth, which differed from the actual state of SOC reserves; 4) The goodness of fit of R2 in GWRK (0.50) was apparently higher than that in RK (0.20). The root mean square error of GWR is 4.58, which was less than the RK (5.35) of RMSE. Additionally, the predicting outcomes obtained using the GWRK reflected the positional information of sampling points, which could make the mapping elaborate.