International Geoscience and
Remote Sensing Symposium
Theme Tag Line
FR1.R14.4
ASSESSING LANDSAT-9 IN IDENTIFYING LITHOLOGY, USING A HYBRID METRIC-LEARNING AND SVM METHOD AGAINST BASELINE ALGORITHMS: A CASE STUDY OF THE WEST AFRICAN CRATON
Michael Appiah-Twum, Haitao Jia, Wenbo Xu, University of Electronic Science and Technology of China, China
Session:
FR1.R14: Remote Sensing Data Applied to Mineral Deposits: A New Era for Critical Raw Material Deposits Studies Oral
Track:
Community-Contributed Sessions
Location:
Room E
Presentation Time:
Fri, 21 Jul, 09:06 - 09:18 Pacific Time (UTC -8)
Session Co-Chairs:
Ana Cláudia Teodoro, Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto; Institute of Earth Sciences (ICT), Pole of University of Porto and Joana Cardoso-Fernandes, Department of Geosciences, Environment and Land Planning, Faculty of Sciences, University of Porto; Institute of Earth Sciences (ICT), Pole of University of Porto