Determining match pairs among disordered images is a prerequisite for constructing tie points and control networks for the bundle adjustment of planetary remote sensing images. The efficiency and accuracy of determining image match pairs greatly affect the performance of generating planetary mapping products and three-dimensional models. However, existing methods for determining image match pairs in the field of planetary mapping generally use exhaustive methods (such as the USGS ISIS software), which are extremely inefficient when processing a large number of images. This paper proposes an efficient method of image overlapping relationship analysis based on the spatial index of KD tree fast search for disordered and large-scale asteroid images. The algorithm first calculates the three-dimensional coordinates of the image center point, constructs a KD tree data structure based on the three-dimensional coordinates of each image center, and then uses the KD tree fast search algorithm to quickly find the image overlapping relationships within the spec-ified spatial range. For situations where the entire celestial body only occupies a local area of the remote sensing image during the approach stage of asteroids, the center of the effective pixels in the image is calculated by the ray intersection of sampling points. In this study, the image data from asteroid exploration missions such as Bennu, Vesta, and Ryugu are used for experiments, and the proposed image match pairs determination algorithm is systematically compared with the corre-sponding modules of USGS ISIS in order to evaluate its performance in terms of efficiency and accuracy. The results show that when processing more than a thousand images, the proposed method is two to three orders of magnitude higher in efficiency than the corresponding module in USGS ISIS while ensuring the correctness of the image overlapping relationships and the accuracy of bundle adjustment, with the advantage becoming clearer as the amount of data increases. At the same time, according to the obtained image match pairs, images that meet the requirements of Stereo Photoclinometry can be quickly and preferably selected, effectively improving the quality of 3D reconstruction models of asteroid images.