Laser-induced breakdown spectroscopy combined with KNN for tracing study of soils from different regions

Junjie Chen; Xiaojian Hao; Haoyu Jin; Shuaijun Li; Biming Mo; Zheng Wang

doi:10.1117/12.3003982

18 December 2023 Laser-induced breakdown spectroscopy combined with KNN for tracing study of soils from different regions

Junjie Chen, Xiaojian Hao, Haoyu Jin, Shuaijun Li, Biming Mo, Zheng Wang

Author Affiliations +

Proceedings Volume 12962, AOPC 2023: Optical Spectroscopy and Imaging; and Atmospheric and Environmental Optics; 1296203 (2023) https://doi.org/10.1117/12.3003982
Event: Applied Optics and Photonics China 2023 (AOPC2023), 2023, Beijing, China

Abstract

Mining heavy metal ore deposits may lead to an increase in heavy metal element content in surrounding soils, which could pose irreversible harm to the ecological environment and human health. Therefore, analyzing and classifying soils from different mining areas is of great significance and can provide reference for soil management and environmental pollution control. Laser-induced breakdown spectroscopy (LIBS) has gradually become a research hotspot in soil detection due to its fast and pre-treatment-free characteristics. However, traditional LIBS technology has problems such as low sensitivity, high noise, and poor repeatability, which affect its accuracy. Therefore, this paper proposes a soil classification method based on Principal Component Analysis (PCA) of LIBS technology coupled with K-Nearest Neighbor algorithm (KNN). This method first conducts data standardization and PCA pre-processing to eliminate redundant information and improve signal-to-noise ratio. Then, autonomous sampling technology is used to design the KNN machine learning algorithm structure to generate continuous analytical networks for training and testing sets. Finally, the results show that the soil classification accuracy of the PCA-KNN machine learning model can reach 97.531%, proving that the combination of LIBS technology and PCA-KNN can achieve rapid and accurate classification of soils from different mining areas. Therefore, this method has the significance of providing new ideas and methods for soil classification in different regions.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Junjie Chen, Xiaojian Hao, Haoyu Jin, Shuaijun Li, Biming Mo, and Zheng Wang "Laser-induced breakdown spectroscopy combined with KNN for tracing study of soils from different regions", Proc. SPIE 12962, AOPC 2023: Optical Spectroscopy and Imaging; and Atmospheric and Environmental Optics, 1296203 (18 December 2023); https://doi.org/10.1117/12.3003982

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KEYWORDS

Soil contamination

Laser induced breakdown spectroscopy

Soil science

Principal component analysis

Machine learning

Pollution control

Laser applications

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