Abstract: By using multi-source remote sensing image data from Mars Orbiters, the technical framework for Martian surface topography fine 3D modeling and automatic classification was developed. The high-resolution terrain of Tianwen-1 landing area was made by combining the photogrammetry and the Shape-from-Shading (SFS) methods, and high-resolution images were used to classify and analyze the topography category and distribution of the land area using a deep convolution neural network. The profile analysis results show that the high-precision terrain data presented in this paper are highly consistent with high resolution digital elevation model (DEM) products published by China and US, resulting in the mean elevation errors equal to 1.866 m and 1.074 m, respectively. Furthermore, it can be seen from the comprehensive terrain and morphology analysis by using the orbiter remote sensing images that near the landing point the slope is less than 3° and the fluctuation of the surface is less than 30 cm. This indicates that the overall terrain of Tianwen-1 landing area is flat and the morphology category is relatively single, which meets the requirements of the probe’s safe landing. The terrain produced by Tianwen-1 high-resolution camera data and classification results, which can be effectively applied to the morphological analysis of the landing and patrol areas, when combined with multi-source Mars remote sensing data such as HiRISE, can provide important basic data and reference information for subsequent scientific explorations of Zhurong patrol.