NAOC Open IR
Lunar impact crater identification and age estimation with Chang'E data by deep and transfer learning
Yang, Chen1,2; Zhao, Haishi3; Bruzzone, Lorenzo4; Benediktsson, Jon Atli5; Liang, Yanchun3; Liu, Bin2; Zeng, Xingguo2; Guan, Renchu3; Li, Chunlai2; Ouyang, Ziyuan1,2
2020-12-22
Source PublicationNATURE COMMUNICATIONS
ISSN2041-1723
Volume11Issue:1Pages:15
AbstractImpact craters, which can be considered the lunar equivalent of fossils, are the most dominant lunar surface features and record the history of the Solar System. We address the problem of automatic crater detection and age estimation. From initially small numbers of recognized craters and dated craters, i.e., 7895 and 1411, respectively, we progressively identify new craters and estimate their ages with Chang'E data and stratigraphic information by transfer learning using deep neural networks. This results in the identification of 109,956 new craters, which is more than a dozen times greater than the initial number of recognized craters. The formation systems of 18,996 newly detected craters larger than 8km are estimated. Here, a new lunar crater database for the mid- and low-latitude regions of the Moon is derived and distributed to the planetary community together with the related data analysis. Using Chang'E data, the authors here identify more than 109,000 previously unrecognized lunar craters and date almost 19,000 craters based on transfer learning with deep neural networks. A new lunar crater database is derived and distributed to the planetary community.
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province
DOI10.1038/s41467-020-20215-y
WOS KeywordLATE HEAVY BOMBARDMENT ; OPTICAL MATURITY ; MARE BASALTS ; CLASSIFICATION ; CATALOG ; IMAGES ; ORIGIN
Language英语
Funding ProjectNational Natural Science Foundation of China[61572228] ; National Natural Science Foundation of China[61972174] ; Key Laboratory of Lunar and Deep Space Exploration[LDSE201906] ; Science-Technology Development Plan Project of Jilin Province of China[20190303006SF] ; Science-Technology Development Plan Project of Jilin Province of China[20190302107GX] ; Industrial Innovation Special Funds Project of Jilin Province[2019C053-5] ; Industrial Innovation Special Funds Project of Jilin Province[2019C053-7]
Funding OrganizationNational Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Key Laboratory of Lunar and Deep Space Exploration ; Key Laboratory of Lunar and Deep Space Exploration ; Science-Technology Development Plan Project of Jilin Province of China ; Science-Technology Development Plan Project of Jilin Province of China ; Industrial Innovation Special Funds Project of Jilin Province ; Industrial Innovation Special Funds Project of Jilin Province
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000603077300001
PublisherNATURE RESEARCH
Citation statistics
Document Type期刊论文
Identifierhttp://ir.bao.ac.cn/handle/114a11/79896
Collection中国科学院国家天文台
Corresponding AuthorYang, Chen; Guan, Renchu; Li, Chunlai
Affiliation1.Jilin Univ, Coll Earth Sci, Changchun 130061, Peoples R China
2.Chinese Acad Sci, Natl Astron Observ, Key Lab Lunar & Deep Space Explorat, Beijing 100101, Peoples R China
3.Jilin Univ, Coll Comp Sci & Technol, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China
4.Univ Trento, Dept Informat Engn & Comp Sci, I-38122 Trento, Italy
5.Univ Iceland, Elect & Comp Engn, IS-101 Reykjavik, Iceland
Recommended Citation
GB/T 7714
Yang, Chen,Zhao, Haishi,Bruzzone, Lorenzo,et al. Lunar impact crater identification and age estimation with Chang'E data by deep and transfer learning[J]. NATURE COMMUNICATIONS,2020,11(1):15.
APA Yang, Chen.,Zhao, Haishi.,Bruzzone, Lorenzo.,Benediktsson, Jon Atli.,Liang, Yanchun.,...&Ouyang, Ziyuan.(2020).Lunar impact crater identification and age estimation with Chang'E data by deep and transfer learning.NATURE COMMUNICATIONS,11(1),15.
MLA Yang, Chen,et al."Lunar impact crater identification and age estimation with Chang'E data by deep and transfer learning".NATURE COMMUNICATIONS 11.1(2020):15.
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