Global detection of large lunar craters based on the CE-1 digital elevation model

Craters, one of the most significant features of the lunar surface, have been widely researched because they offer us the relative age of the surface unit as well as crucial geological information. Research on crater detec- tion algorithms （CDAs） of the Moon and other planetary bodies has concentrated on detecting them from imagery data, but the computational cost of detecting large craters using images makes these CDAs impractical. This paper presents a new approach to crater detection that utilizes a digital elevation model instead of images; this enables fully automatic global detection of large craters. Craters were delineated by terrain attributes, and then thresholding maps of terrain attributes were used to transform topographic data into a binary image, finally craters were detected by using the Hough Transform from the binary image. By using the proposed algorithm, we produced a catalog of all craters ≥ 10 km in diameter on the lunar surface and analyzed their distribution and population characteristics.