ML in Geological Mapping | Sponsored by NRCan

Leads / Advisors

Hazen Russell | Lead Sedimentologist GS

William Parkinson | Lead Technical Product Manager, EarthDaily Analytics

~Nicolas Benoit | Lead Hydrogeologist, GSC

Overview

• Challenge - mapping geological materials that can have overlapping spectral signals and landscape positions. Extraction of irregular landform shapes and sizes that have inconsistent composition, moisture regime, and vegetation.

• Tools - Machine Learning in Python using scikit-learn, TensorFlow or PyTorch algorithms (classification, regression, clustering, Convolutional Neural Network and more) and Geostatistic (spatial covariance, interpolation, simulation, scaling and uncertainty characterization).

• The goal is to build an understanding of the challenge of replacing abstract cognitive analysis with ML analysis.

Top Contributors

• Debjani Mukherjee

• Afhsin Amini

A bit about our experience

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