In collaboration with USGS, MITRE, and NASA’s Jet Propulsion Laboratory, DARPA launched the AI for Critical Mineral
Assessment Competition, which solicits innovative solutions for automatically georeferencing scanned or raster
maps and extracting their features. DARPA and USGS will apply lessons learned from the competition to future improvement efforts.
The competition will include the following two, independent challenges. For each of the two challenges,
DARPA will award $10,000 for the first prize, $3,000 for the second prize, and $1,000 for the third prize in December 2022.
Map Georeferencing Challenge
August 15 - 26
Automated map georeferencing is a difficult task as most USGS maps are not digitized and may be in a
multitude of historical coordinate projection systems. Furthermore, the quality of features on scanned
maps, critical for the identification of control points for alignment, can vary greatly. Participants
will receive a dataset of 1,000 or more maps of various types for training and validation. The goal of
the challenge is to accurately geolocate a map of unknown location and coordinate system by fitting
coordinate points that can be referenced to known locations in one or more base maps.
Map Feature Extraction Challenge
Automated map feature extraction is a difficult task because map features (polygons, points, lines, text)
often overlap and are sometimes discontinuous. Not only do the features come in all shapes and sizes, but
the same feature type can be depicted in different maps using different symbols or patterns. This makes
it challenging to create a universal identifier for even a single feature such as a mine location or
mineral resource tracts. Participants will be provided a training set consisting of maps with each
legend item labeled and characterized (as point, line, or polygon) and a binary pixel map reflecting
the feature’s coverage in the map. The goal of the challenge is to identify all features in a map that
appear in the map’s legend.
DARPA may close registration early based on a number of conditions.