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LIU Fangchao, ZHANG Li, GUO Dijun, LIU Bin, XIE Bin, LYU Ying-Bo, CHEN Jian, LING Zongcheng. Impact Crater Database of 10 Landing Regions from Apollo and Chang’E Missions: Construction and Distribution Patterns of Small Impact Crater Databases (in Chinese). Chinese Journal of Space Science, 2026, 46(3): 1-14 doi: 10.11728/cjss2026.03.2025-0135
Citation: LIU Fangchao, ZHANG Li, GUO Dijun, LIU Bin, XIE Bin, LYU Ying-Bo, CHEN Jian, LING Zongcheng. Impact Crater Database of 10 Landing Regions from Apollo and Chang’E Missions: Construction and Distribution Patterns of Small Impact Crater Databases (in Chinese). Chinese Journal of Space Science, 2026, 46(3): 1-14 doi: 10.11728/cjss2026.03.2025-0135
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Impact Crater Database of 10 Landing Regions from Apollo and Chang’E Missions: Construction and Distribution Patterns of Small Impact Crater Databases

doi: 10.11728/cjss2026.03.2025-0135 cstr: 32142.14.cjss.2025-0135
  • 1.

    School of Space Science and Technology, Shandong University, Weihai 264209

  • 2.

    School of Low-altitude Science and Engineering, Shandong University, Weihai 264209

  • 3.

    State Key Laboratory of Solar Activity and Space Weather, National Space Science Center, Chinese Academy of Sciences, Beijing 100190

  • 4.

    State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101

  • Received Date: 2025-07-31
  • Rev Recd Date: 2026-03-09
    • Available Online: 2026-03-12
    Abstract
  • Among the celestial bodies within the solar system, the Moon maintains the most pristine conditions of impact craters. Some landing sites on the lunar surface have in-situ exploration data and experimental measurement results from the returned samples, providing distinguished meanings to understand the impact events and their reshaping effects on the lunar surface. Small craters play a significant role in the formation and evolution of lunar regolith. However, existing lunar impact crater databases lack comprehensive coverage of small-scale impact craters with diameters less than 100 m. Therefore, this study produced ten mosaic images of 20 km×20 km in width, using the high-resolution Lunar Reconnaissance Orbiter Camera Narrow Angle Camera images acquired under solar incidence angles between 50° and 70°. These images cover ten lunar landing sites, including six Apollo missions and four Chang’E missions. An improved YOLO11+SAHI deep learning model was then applied to automatically extract craters with diameters ≥15 m within these regions. After manual verification, a high-quality crater database containing 359844 records was constructed. Compared with existing datasets, the proposed database demonstrates superior crater completeness. Based on this database, the density distribution and diameter-frequency characteristics of small-sized impact craters were further calculated and analyzed. This dataset can provide robust support for studies of lunar geological chronology, impact flux evolution, surface process, and sample interpretation. In addition, it supplies a valuable training and validation resource for future artificial intelligent models of detecting the impact craters.

     

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