In recent decades, the surface mass balance (SMB) and the calving of outlet glaciers have accelerated the mass loss of the Greenland Ice Sheet (GrIS), with SMB’s contribution continuing to increase. Therefore, determining SMB’s spatiotemporal distribution is critical for understanding the mass balance of the GrIS. Currently, the regional climate model and the remote sensing observation of outlet glacier flux gates serve as two primary calculation methods for the GrIS’s SMB. However, the former method results in large uncertainties in the SMB simulation. The latter method can only indirectly estimate the overall SMB value for the upper reaches of the flux gate, failing to reflect the spatial distribution of SMB. This study proposed a method for estimating the GrIS’s SMB based on remote sensing data and ice flux divergence, obtaining the relatively accurate spatial distribution of SMB. First, the interannual variation in the elevation of the GrIS was derived from ICESat-2 laser altimetry data. Second, based on MEaSUREs-derived glacier flow velocity data and BedMachine-derived ice thickness data, the ice flux divergence was calculated using the pixel-based finite difference method to estimate the GrIS’s elevation changes caused by glacier flow. The GrIS’s elevation changes caused by SMB were then obtained by subtracting the elevation changes caused by glacier flow from the ICESat-2 elevation data. Third, through the firn densification model, the elevation changes caused by SMB were converted into mass changes to reflect the interannual spatial distribution of the GrIS’s SMB. The proposed method was applied to estimate the spatial distribution of the GrIS’s SMB in 2019 and 2020, yielding relatively high accuracy (RMSE=0.519 m w.e.) in comparison with the measured SMB from the observation station, and outperforming the regional climate model (RMSE=0.565 m to 0.877 m w.e.), ultimately demonstrating its reliability.