A review on advancements in lithological mapping utilizing machine learning algorithms and remote sensing data
Author:
Publisher
Elsevier BV
Subject
Multidisciplinary
Reference94 articles.
1. Improving lithological mapping by SVM classification of spectral and morphological features: the discovery of a new chromite body in the mawat ophiolite complex (Kurdistan, NE Iraq);Othman;Rem. Sens.,2014
2. Optimized lithological mapping from multispectral and hyperspectral remote sensing images using fused multi-classifiers;Pal;Rem. Sens.,2020
3. Hyperspectral remote sensing in lithological mapping, mineral exploration, and environmental geology: an updated review;Peyghambari;J. Appl. Remote Sens.,2021
4. Lithologic mapping of a forested montane terrain from landsat 5 TM image;Mahmood;Geocarto Int.,2018
5. Lithological mapping in Sangan region in Northeast Iran using ASTER satellite data and image processing methods;Rezaei;Geol. Ecol. Landsc.,2020
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Improving Rock Classification with 1D Discrete Wavelet Transform Based on Laboratory Reflectance Spectra and Gaofen-5 Hyperspectral Data;Remote Sensing;2023-11-13
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