Research topic
Geochemistry and Geologic Mapping
Physical Sciences → Computer Science → Artificial Intelligence
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 Services1 Research outputs |
Geoecology and Carbonate Sedimentology1 Research outputs |
Global Change Impacts and Adaptation1 Research outputs |
Ecosystem Co-Design1 Research outputs |
Research Data Service1 Research outputs |
Submarine Groundwater Discharge1 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
1 Research outputsDr. Donata Monien
1 Research outputsFinn Opätz
1 Research outputsDr. Philipp Gies
1 Research outputsSebastian Swirski
1 Research outputsDr. Sara Todorović
1 Research outputsThe 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.