Digital orthophoto map products and automated generation algorithms of Chinese optical satellites

Orthorectification is the foundation for the subsequent processing, analysis, and application of satellite remote sensing images. However, the accuracy of the autonomous geo-positioning of the optical satellite data cannot reach 1—2 pixels at present. Ground Control Points (GCPs) are still required for correcting the geometric model to generate Digital Orthophoto Map (DOM) products. This study introduces the DOM products of Chinese optical satellites and automated processing algorithms independently developed by China Remote Sensing Satellite Ground Station. Given the current situation, characteristics, and application requirements of the Chinese optical satellite data, a complete and automated DOM generation algorithm has been developed. It consists of several key steps and techniques, including automated GCP collection via accurate image registration, optimization of image geometry model, image orthorectification, pixel-wise geometric uncertainty estimation, pixel-wise solar irradiation and satellite observation angle calculation, and image division and encoding based on a global or regional geographic grid. (1) Given that the conventional affine transformation correction in the image space for the Rational Polynomical Coefficients (RPC) model cannot achieve satisfactory accuracy when applied to perform a geometric model if the swath width of the image is large or the geometric calibration accuracy is insufficient, a full-parameter optimization method of RPC model based on L1-norm constrained least squares (L1LS) is applied to improve the accuracy of the geometric model. (2) A novel block adjustment method that considers the accuracy of GCPs is proposed. When the GCPs obtained from the reference image with the low spatial resolution are used to correct the geometric model, the random error of the geometric model can be reduced through multiple observations under the premise of meeting the geometric constraints of the reference image, thereby improving the geo-positioning accuracy of the image. (3) Based on uncertainty propagation theory, the per-pixel geometric uncertainty is derived from the geometric model, the Digital Elevation Model (DEM) data, and the residual errors of GCPs to enable the geometric accuracy traceability of DOM products. When applied to GF-1 MSS, GF-1 WFV, GF-6 PAN, HJ-2A CCD4, CB-4A MSS, and ZY-1E PAN images, the L1LS-based full-parameter optimization method of the RPC model outperforms the conventional affine transformation correction in the image space for the RPC model, particularly for the images with a large field of view. The proposed block adjustment approach considering the accuracy of GCPs achieves higher accuracy than the ordinary block adjustment method when GCPs are obtained from a reference image with a resolution (10—15 m) lower than that of the target image (2—2.5 m).Conclusion The experimental results show that the algorithm in this study can be used for the large-scale production of orthophoto products. The field-measured checkpoints distributed all over China show that the absolute geometric accuracy of the produced 16 m-resolution DOM products can achieve high accuracy within two pixels. © 2023 Science Press. All rights reserved.