Datasets for "Unexplored Antarctic meteorite collection sites revealed through machine learning"

This archive provides datasets related to the following publication:

V. Tollenaar, H. Zekollari, S. Lhermitte, D. Tax, V. Debaille, S. Goderis, P. Claeys, F. Pattyn, Unexplored Antarctic meteorite collection sites revealed through machine learning. Science Advances 8, eabj8138 (2022). DOI: 10.1126/sciadv.abj8138

Contact: Veronica Tollenaar, [e-mail]

Users should cite the original publication when using all or part of the data. 

About the datasets: it includes a shapefile with the outline of the 613 Meteorite Stranding Zones (Fig. 7, "613MSZs.zip"), the observations used for classification, and the continent-wide probability to find meteorites (at 450-meter resolution, Fig. 5, "positive_classified.nc"). References to the literature are provided in the corresponding publication. Meteorite locations are based on the Meteoritical Bulletin Database (available at https://www.lpi.usra.edu/meteor/).

- bias_above200m1kmbuff_expanded_dissolved: shapefile of polygons of unlabelled observations
- meteorite_locations_raw.csv: contains locations of meteorite finds as defined in the meteoritical bulletin consulted on 05/07/2019
- meteorite_types.csv: contains meteorite names and types as defined in the meteoritical bulletin consulted on 05/07/2019
- validation_neg.csv: contains locations of negative observations used for validation
- TEST_neg.csv: contains locations of negative test observations
- TEST_pos.csv: contains locations of positive test obesrvations
- MSZs_ranked: shapefile of ranked meteorite stranding zones
- Test_neg4326: shapefile of locations used as negative test data
- Cal_neg4326: shapefile of locations used as negative calibration/validation data
- TestMSZs_pos4326: shapefile of locations used as positive test data in MSZ-level assesment
- 613MSZs: shapefile of outlines of meteorite stranding zones
- positive_classified.nc: netcdf of positive classified observations with their estimated a posteriori probabilities