PROGRESS IN GEOGRAPHY ›› 2015, Vol. 34 ›› Issue (3): 330-.doi: 10.11820/dlkxjz.2015.03.008

• Orginal Article • Previous Articles     Next Articles

A global inventory of lunar craters: identification, classification, and distribution

Jiao WANG1,2, Weiming CHENG1, Chenghu ZHOU1   

  1. 1. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Online:2015-03-25 Published:2015-03-25


The most widespread geomorphic units on lunar surface are craters. In this article, we use a remote sensing image and DEM model from the Cang'E-1 satellite as data source to study craters on the lunar surface. First, an integrated procedure that uses a remote sensing image, DEM and its derived products (slope, curvature) to extract the edifice of craters is applied. At a scale of 1: 2500000 edifice boundaries are manually defined by searching for breaks in slope around the base and there are a total of 106030 impact craters identified. Then we present two methods to evaluate the extraction accuracy and cumulative crater frequency. The result shows that the extraction error is less than 12 percent and the cumulative crater frequency curves from both sets of data obtained through these two methods are similar. Second, all the craters are divided into six groups including the ghost, walled plain, ring plain, crater plain, bowl-shaped, and dimple craters based on previous studies. A corresponding interpretation symbol database is established to illustrate the appearance of craters on a digital image. Finally, some statistical data on different types of craters across the lunar surface are generated. Characteristics such as number, density, and spatial distribution are calculated in ArcGIS and SPSS. We find that the bowl-shaped craters are the major type of all the craters and there is a strong inverse correlation between the number of craters and their diameter. The data provided herein is by far the most comprehensive lunar craters data so that it offers an opportunity to systematically study the impact mechanisms, impact effects, and evolutionary history of craters on lunar surface.

Key words: Chang'E-1 satellite, crater classification, detection, spatial analysis