High Accuracy Georeferencing of GF-6 Wide Field of View Scenes Toward Analysis Ready Data

Analysis ready data (ARD) has recently become a popular standard for medium-resolution satellite images. The most representative datasets, namely Sentinel-2 Level-2A products and Landsat Collection 2 Level-2 Science Products, have met ARD standards, with public access. The Chinese Gaofen (GF) series Level-1A wide field of view (WFV) product, which has a similar ground sampling distance (GSD) to Sentinel-2 Level-2A products, is open to the public for its scenes and rational function model (RFM). However, the lower geometric processing accuracy of WFV products of approximately 3-pixel geolocation deviation restricts their wide application and further development toward ARD. The causes of low accuracy are twofold, namely the impact of calibration errors and the inaccuracy of the exterior orientation parameters. In terms of improving the accuracy of RFM, bundle adjustment and the bias compensation model (BCM) are currently the most widely accepted methods. However, existing approaches do not account for the imaging characteristics of WFV scenes, which are only for narrow field-of-view scenes and do not help with nonlinear internal distortions. To address the shortcomings of these methods, a joint orientation method for WFV cameras is proposed in this study. Owing to the high level of geometric accuracy of Sentinel-2 Level-1C reference scenes, this study analyzed the expression of WFV camera attitude errors on the image side. A polynomial exterior orientation model suitable for WFV cameras is also provided. We performed a refined calibration of the nonlinear internal distortions using multitemporal GF-6 Level-1A WFV images because of the additional error introduced by the cross-track inconsistency of the Sentinel-2 reference data. The method developed in this study has been experimentally verified to achieve satisfactory geometric positioning accuracy with GF-6 WFV products from 3-pixel to 0.3-pixel (5 m). This study allows optimization of the geometric performance of GF-6 Level-1A WFV products to the level of Sentinel-2 Level-1C products, which is of considerable importance in developing GF WFV images to ARD.