UniFast: A Universal Geometric Correction Approach for Chinese Virtual Constellation of Wide-Swath Optical Satellites

The Chinese Center for Resources Satellite Data and Application (CRESDA) has released wide-swath optical imagery from GF-1, GF-6, and HJ-2A/B satellites for free, forming a virtual constellation capable of near-daily coverage of the national land surface. However, their geolocation accuracy typically exhibits errors of 2~3 pixels, which is insufficient for generating high-quality Analysis Ready Data (ARD). This study proposed a universal and efficient method, referred to as UniFast, for the accurate geometric correction of these wide-swath optical imagery. The UniFast has three key innovations: (1) integrated modeling and correction of internal nonlinear distortions and external attitude errors, (2) use of globally available Landsat imagery as reference data instead of geometric calibration field and (3) generalized applicability to GF-1/6 and HJ-2A/B satellite imagery. Experiments are carried out at two test sites, including a mountainous area in southeastern China and a texture less desert in western China. This study involves 26 scenes images downloaded from CRESDA, which shows that initial RMSEs reach up to 5.64 pixels. After applying the UniFast, all sensors achieve sub-pixel geolocation accuracy, with absolute errors consistently below one pixel. Specifically, the relative RMSEs among multi-satellites are reduced from a maximum of 3.53 pixels to below 0.3 pixels in the mountainous site, and from 4.99 pixels to below 0.5 pixels in the desert site. These results demonstrate the effectiveness and versatility of the UniFast, which overcomes a critical bottleneck in global change studies utilizing remote sensing images from the Chinese virtual constellation.