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10 February 2023 Research on unsupervised lithology classification based on dimension reduction data: a case of Jimusar area of Xinjiang in China
Yuntao Kang
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Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 125521O (2023) https://doi.org/10.1117/12.2667445
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China
Abstract
The classification and extraction of lithology is an important research direction of remote sensing geological survey, but lithology is different from other objects, often because of terrain differences, natural weathering and other factors, spectral differences are not obvious, simple unsupervised classification may not have good results even if the number of iterations increases. For Landsat8 data, we adopt two common data dimension reduction methods, classify the results by K-means unsupervised classification to divide lithology, compare the results with the dimension reduction, and obtain good experimental results, which can be used as a good method to quickly understand the geological situation of the study area.
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Yuntao Kang "Research on unsupervised lithology classification based on dimension reduction data: a case of Jimusar area of Xinjiang in China", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 125521O (10 February 2023); https://doi.org/10.1117/12.2667445
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KEYWORDS
Image classification
Principal component analysis
Remote sensing
Image enhancement
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