Replacement Sensor Model Generation for a Long High-Resolution Satellite Image Strip

Many high-resolution satellite images are acquired in the strip mode, in which the imaging direction is aligned with the satellite trajectory. A long strip image is often sliced into several scenes before delivery, and customers preprocess each scene with auxiliary data before their applications. Sensor model information is often provided for each scene in the form of rational polynomial coefficients (RPCs). The original RPCs of each scene are erroneous, and should be bias-compensated using ground reference data or ground control points. In this study, we propose the use of single RPCs for long image strips. However, a simple replacement of the physical sensor model using RPCs for the entire strip may cause large errors, because RPCs do not model large satellite attitude changes. Therefore, we applied the fitting of the satellite attitude to a linear equation before RPCs generation for a long-strip image. The test was conducted for three Kompsat-3A image strips consisting of multiple scenes, where one strip shows large satellite attitude changes. From the experiments, the RPCs generated for the whole image strip showed large errors compared to the strip adjustment; however, the proposed method could reduce the errors to an accuracy comparable to that of scene-based RPCs.