Automatic Crater Detection Tool for Moon, Mars, and Mercury

Users can select among three celestial bodies – Mars, Moon, or Mercury – by clicking on the respective options. The software offers two input modes. In "single image" mode, users directly enter the image paths.

In "batch" mode, the program processes all TIFF files within a specified folder. Input images should be GeoTIFF files in Mercator projection to ensure circular shapes for impact craters.The automatic crater detection process begins with a click of the “Start” button.The right-hand viewing interface shows a preview image displaying the crater detection results. In batch mode, the “Previous Image” and “Next Image” buttons allow sequential preview of all images and detection results.Data and OutputInput images should be in GeoTIFF format with Mercator projection centered on the equator to ensure accurate detection.Output results are saved in the specified output path in both shapefile and TXT file formats.

The attribute table of the shapefile includes the crater central latitude and longitude (‘Lon’ and ‘Lat’) and the geodesic diameter in meters (‘Dia’). The projection distortion caused by projection has been considered and corrected through computation within the tool. As the craters are extracted in Mercator projection, the corresponding information is provided to better correspond with the images: ‘X_Merc’ and ‘Y_Merc’ for the x and y coordinates in Mercator and ‘D_Merc’ for the distorted diameter measured in the Mercator projection.

The confidence score (‘Score’), ranging from 0 to 1, is also provided; higher values indicate greater confidence in the crater detection results. Additionally, a TXT file containing information identical to the shapefile attributes is generated. If an error occurs during the detection process, the names of the erroneous images and the reasons are recorded in an Error.txt file.VersionThe ACD Tool runs on Windows and offers both CPU and GPU versions, allowing users to choose the version that best fits their needs.

For faster performance, the GPU version is recommended if a graphics card is available. Otherwise, the CPU version is suitable for systems without a dedicated graphics card.DatasetsOur dataset includes annotated craters on the Moon, Mars, and Mercury. The initial annotations were sourced from publicly available online databases and were further supplemented with manual annotations.

For the Moon, LROC WAC images (Speyerer, 2011; Wagner, 2015) and SELENE TC images (Kato et al., 2008) were annotated based on the studies of Robbins (2019) and Wang & Wu (2019), respectively, while LROC NAC images were fully manually annotated. For Mars, crater annotations for the THEMIS-IR mosaic (Edwards et al., 2011) followed the work of Robbins & Hynek (2012), and additional manual annotations were applied to CTX (Malin et al., 2007) and HiRISE (McEwen et al., 2007) images.

For Mercury, the MDIS global mosaic (Becker et al., 2009; Hawkins III et al., 2009) underwent complete manual annotation and verification.The dataset includes craters of various sizes and resolutions. On the Moon, the LROC WAC dataset has a resolution of 150 m/pixel, covering 186,302 craters with diameters ranging from 1,000 to 46,692 meters. The LROC NAC dataset, with a resolution of 1.1 m/pixel, includes 34,012 craters with diameters between 7 and 307 meters.

The SELENE TC dataset has a resolution of 6.2 m/pixel and includes 54,563 craters with diameters between 120 and 1,949 meters. For Mars, the THEMIS-IR dataset has a resolution of 150 m/pixel and includes 121,517 craters with diameters ranging from 994 to 47,322 meters. The CTX dataset has a resolution of 5 m/pixel and includes 6,678 craters with diameters between 21 and 2,467 meters.

The HiRISE dataset, with a resolution of 0.5 to 1 m/pixel, includes 5,978 craters with diameters ranging from 2 to 144 meters. For Mercury, the MDIS dataset has a resolution of 166 m/pixel and includes 17,749 manually annotated craters with diameters ranging from 996 to 26,347 meters.The dataset is organized by body, stored in YOLO annotation format, and located in the respective subfolders within the “Datasets” directory.

Each body folder contains “images” and “labels” folders, which store crater images and position annotations, respectively. Within each folder, data is further divided into “train” and “val” subfolders for training and validation.