Accuracy comparison of various remote sensing data in lithological classification based on random forest algorithm
Author:
Affiliation:
1. School of resources and Geosciences, China University of Mining and Technology, Xuzhou, China
Funder
Priority Academic Program Development of Jiangsu Higher Education Institutions
Publisher
Informa UK Limited
Subject
Water Science and Technology,Geography, Planning and Development
Link
https://www.tandfonline.com/doi/pdf/10.1080/10106049.2022.2088859
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1. Detecting Sirex noctilio grey-attacked and lightning-struck pine trees using airborne hyperspectral data, random forest and support vector machines classifiers
2. Synergy of Remote Sensing Data for Exploring Hydrothermal Mineral Resources Using GIS-Based Fuzzy Logic Approach
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4. Lithological mapping in the Central Eastern Desert of Egypt using ASTER data
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