A Spatial Data-Driven Approach for Mineral Prospectivity Mapping

A Spatial Data-Driven Approach for Mineral Prospectivity Mapping

Mineral prospectivity mapping is a crucial technique for discovering new economic mineral deposits. However, detailed knowledge-based geological exploration and interpretations generally involve significant costs, time, and human resources. In this study, an ensemble machine learning approach was te...

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Bibliographic Details
Main Authors: Indishe P. Senanayake, Anthony S. Kiem, Gregory R. Hancock, Václav Metelka, Chris B. Folkes, Phillip L. Blevin, Anthony R. Budd
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Remote Sensing
Subjects:
machine learning
maximum-likelihood classification
mineral prospectivity
random forest
support vector machine
Online Access:https://www.mdpi.com/2072-4292/15/16/4074

Internet

https://www.mdpi.com/2072-4292/15/16/4074

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