A New Global Color Image Dataset and Reference Frame for Mars by Tianwen-

Global-scale Mars remote-sensing image datasets with accurate and consistent spatial positions contain a wealth of information on its surface morphology, topography, and geological structure. These data are fundamental for scientific research and exploration missions of Mars. Prior to China's first Mars exploration mission (Tianwen-1), none of the available global color-image maps of Mars with a spatial resolution of hundreds of meters were true-color products. On the other hand, there is currently a lack of global optical image datasets on a scale of several tens of meters with high-precision positioning and consistency that can be served as a reference frame for Mars. Global remote sensing of Mars is one of the primary scientific goals of Tianwen-1. As of July 25, 2022, The Moderate Resolution Imaging Camera (MoRIC) onboard the orbiter has obtained 14,757 images, which have allowed acquiring global stereo images of the entire Martian surface. Additionally, the Mars Mineralogical Spectrometer (MMS) has returned 325 strips of visible and near-infrared spectral measurement data. These measurement data have laid the foundation for the development of a high-resolution global color-image map of Mars with high positioning accuracy and internal consistency. After processing of radiometric calibration (atmospheric correction, photometric correction and color correction), geometric correction (global adjustments and orthorectification) and global image cartography (global color uniformity, mosaicking and subdivision), the development of the Tianwen-1 Mars Global Color Orthomosaic and datasets based on these data was completed, with a spatial resolution of 76m and a planar position accuracy of 68m (a root mean square (RMS) residual of 0.9 pixels for tie points). This is currently the highest resolution global true color image map of Mars in the world, which can be served as a new Mars geodetic control network and reference frame. It can provide crucial foundational data for Mars scientific research and engineering implementation.