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Research topic

Geochemistry and Geologic Mapping

Physical Sciences → Computer Science → Artificial Intelligence

6 research outputs 0.3% of the institute spectrum

About Geochemistry and Geologic Mapping

This cluster of papers focuses on the application of machine learning, remote sensing, and compositional data analysis techniques for mineral prospectivity mapping. It explores the use of advanced technologies such as ASTER and hyperspectral imaging to identify geological features, geochemical anomalies, and hydrothermal alterations associated with mineralization. The cluster also delves into the challenges and opportunities in using support vector machines, fractal modeling, and statistical analysis for predicting undiscovered mineral deposits.

Keywords

Machine Learning Mineral Prospectivity Remote Sensing Compositional Data Analysis Geological Mapping Hyperspectral Imaging Support Vector Machines Fractal Modeling Geochemical Anomalies Lithological Mapping

Development over time

Year research outputs
2025 4
2016 1
2005 1

Units

Units strongly represented in this topic

Units
Central Services
1 Research outputs
Ecosystem Co-Design
1 Research outputs
Research Data Service
1 Research outputs
Submarine Groundwater Discharge
1 Research outputs

People

Researchers strongly represented in this topic

Here, researchers who have publications in OSIRIS assigned to this spectrum topic are displayed. For better clarity, only a selection is shown.

Alexandra Nozik
Alexandra Nozik
1 Research outputs
Donata Monien
Dr. Donata Monien
1 Research outputs
Finn Opätz
Finn Opätz
1 Research outputs
Philipp Gies
Dr. Philipp Gies
1 Research outputs
Sebastian Swirski
Sebastian Swirski
1 Research outputs
Sara Todorović
Dr. Sara Todorović
1 Research outputs

The assignment of publications to topics is done automatically and may be incomplete or incorrect. If a person does not appear in the list, it does not mean that they could not have contributed to the topic.