1. Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China; 3. National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100012, China
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 detection 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.
Corresponding Author(s):
WANG Xinyuan,Email:xywang@ceode.ac.cn
引用本文:
. Global detection of large lunar craters based on the CE-1 digital elevation model[J]. Frontiers of Earth Science, 2013, 7(4): 456-464.
Lei LUO, Lingli MU, Xinyuan WANG, Chao LI, Wei JI, Jinjin ZHAO, Heng CAI. Global detection of large lunar craters based on the CE-1 digital elevation model. Front Earth Sci, 2013, 7(4): 456-464.
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