Harnessing the Power of Machine Learning for Mapping of Iron Oxide Mineralization using Sentinel Satellite Spectral Imagery-Reference-Cited by-同舟云学术

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Harnessing the Power of Machine Learning for Mapping of Iron Oxide Mineralization using Sentinel Satellite Spectral Imagery

Published:2022-08-16 Issue: Volume: Page:
ISSN:
Container-title:2022 19th International Bhurban Conference on Applied Sciences and Technology (IBCAST)
language:
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Author:

Ahsan Mahboob Muhammad¹,Genc Bekir²,Atif Iqra³

Affiliation:

1. University of the Witwatersrand,Sibanye-Stillwater Digital Mining Laboratory (DigiMine) Wits Mining Institute (WMI),Johennesburg,South Africa

2. University of the Witwatersrand,School of Mining Engineering,Johennesburg,South Africa

3. University of the Witwatersrand,School of Geography, Archaeology and Environmental Studies,Johennesburg,South Africa

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9989533/9990034/09990084.pdf?arnumber=9990084

Reference21 articles.

1. Remote Sensing Studies for Mapping of Iron Oxide Regions, South of Kerman, IRAN

2. Validated spectral angle mapper algorithm for geological mapping: comparative study between QuickBird and Landsat-TM;girouard;XXth ISPRS Congress Geo-Imagery Bridging Continents,2004

3. Selection of Landsat TM band and band-ratio combinations to maximize lithologic information in color composite displays;crippen,1990

4. Using Machine Learning to Map Western Australian Landscapes for Mineral Exploration

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