Potential of random forest machine learning algorithm for geological mapping using PALSAR and Sentinel-2A remote sensing data: A case study of Tsagaan-uul area, southern Mongolia
Geological mapping in remote and geologically complex regions can be substantially improved by integrating remote sensing data with machine learning algorithms. This study evaluates the effectiveness of the Random Forest algorithm for geological mapping in the Tsagaan-uul area of the Khatanbulag anc...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Journal of Asian Earth Sciences: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590056025000155 |
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