DOI: 10.5281/zenodo.14250970
title: Raw planetary images and boulder labels data (as shapefiles) collected during the BOULDERING Marie Skłodowska-Curie Global fellowship

description: This database contains 64 large images of craters on the lunar and martian surfaces and 3 images of boulder fields on Earth (see manuscript https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013 for more information on those terrestrial locations). The data was collected during the BOULDERING Marie Skłodowska-Curie Global fellowship between October 2021 and 2024.

For each image, the boulder outlines within specific tiles within the image were carefully mapped in QGIS. More information about the labelling procedure can be found in the following manuscript (https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JE008013). This dataset differs from the previous dataset included along with the manuscript https://zenodo.org/records/8171052, as it contains more mapped images, especially of boulder populations around young impact structures on the Moon (cold spots). 

For each location, you will find a raster with a .tif format, and three shapefiles:





a boulder-mapping file, which is the manually digitized outline of boulders.




a tiles-completely-mapped file, which depicts the patches/tiles/windows on which the boulder mapping has been conducted.




a global-tiles file, which shows all of the image patches/tiles/windows (pick the term you are the most familiar with) within a raster.



In addition you will find .pkl (which stands for pickle), which contains some information about the patches/tiles/windows if you would need to clip those windows out from the original raster. You can find more information in the way we process this raw data into a format which can be ingested in a deep learning model (see https://zenodo.org/records/14250874) in the two following github repositories (https://github.com/astroNils/YOLOv8-BeyondEarth and https://github.com/astroNils/MLtools). If you don't plan in adding more training data, you can directly used the pre-processed database (see https://zenodo.org/records/14250874).

There are multiple locations/images per planetary body. Cold spots are located on the Moon, but they are saved in a folder of their own. 

Note that the cold spots boulder mapping shapefiles are partially manually mapped, and partially originating from predictions made from a deep learning model (which explains the outline of boulders are predicted within one pixel).

How to cite:

Please refer to the "how to cite" section of the readme file of https://github.com/astroNils/YOLOv8-BeyondEarth.

Structure:

.
└── raw_data/
├── coldspots/
  │  └── image_name/
  │    ├── shp/
  │    │  ├── <image_name>-tiles-completely-mapped.shp
  │    │  ├── <image_name>-boulder-mapping.shp
  │    │  └── <image_name>-global-tiles.shp
  │    └── raster/
  │      └── <image_name>.tif
  ├── earth/
  │  └── image_name/
  │    ├── shp/
  │    │  ├── <image_name>-tiles-completely-mapped.shp
  │    │  ├── <image_name>-boulder-mapping.shp
  │    │  └── <image_name>-global-tiles.shp
  │    └── raster/
  │      └── <image_name>.tif
  ├── mars/
  │  └── image_name/
  │    ├── shp/
  │    │  ├── <image_name>-tiles-completely-mapped.shp
  │    │  ├── <image_name>-boulder-mapping.shp
  │    │  └── <image_name>-global-tiles.shp
  │    └── raster/
  │      └── <image_name>.tif
  └── moon/
    └── image_name/
      ├── shp/
  │    │  ├── <image_name>-tiles-completely-mapped.shp
  │    │  ├── <image_name>-boulder-mapping.shp
  │    │  └── <image_name>-global-tiles.shp
      └── raster/
        └── <image_name>.tif