Downscaling techniques offer the opportunity to utilize coarse-spatial-resolution SIF products for investigating carbon cycles and ecological processes at finer resolutions. Here, we generated a new monthly SIF product, DSIF_EA0.05, at a resolution of 0.05° in East Asia from July 1995 to June 2003. The random forest kriging (RFK) approach was employed, incorporating GOME SIF, AVHRR data, ERA5 climate data, and using the optimal explanatory variables. The unit of SIF is mW m-2 nm-1 sr-1. The selected variables were daily maximum values of air temperature (Tair), skin temperature (Tskin), fraction of absorbed photosynthetically active radiation (fPAR), near-infrared reflectance of vegetation (NIRv), downward shortwave radiation (SRdown), and precipitation. To verify the reliability of DSIF_EA0.05 and the advantages over original GOME SIF, this dataset has been validated with the original GOME SIF, ground gross primary productivity (GPP) data from eight flux sites, and two other SIF products at 1-degree and 0.05-degree resolutions from SCIAMACHY SIF and downscaled SCIAMACHY SIF datasets.