EventsInternational Conference on Advanced Remote Sensing (ICARS 2025)
Published
This submission belongs to the session S4. Remote Sensing for Agriculture, Water and Food Security of the event International Conference on Advanced Remote Sensing (ICARS 2025)
Published date
25 Mar, 2025
Academic Editor
author-avatarFabio Tosti
Citation
Wanying Ding, Shilong Xu, Yuhao Xia, Shengjie Ma, A remote Laser-Induced Breakdown Spectroscopy applied on Cd profiling in the soil, in Proceedings of International Conference on Advanced Remote Sensing (ICARS 2025), Barcelona, 26 March–28 March 2025, MDPI: Basel, Switzerland
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A remote Laser-Induced Breakdown Spectroscopy applied on Cd profiling in the soil

1. National University of Defense Technology, China
Abstract

As a hazardous heavy metal element, cadmium can migrate in the soil and be absorbed by crops, which may seriously jeopardize human kidneys and other systems through the food chain, posing a great threat to human health. In recent years, with the rapid development of industry and the frequent use of agrochemicals, soil heavy metal pollution has become increasingly serious, forcing the degradation of arable land and affecting the safety of food quality. Therefore, rapid, real-time, and accurate monitoring of Cd contamination in soil is crucial. In this regard, we propose a dual-pulse-based remote laser-induced breakdown spectroscopy (LIBS ) combined with chemometrics for the quantitative detection of soil Cd content, which can be used for remote elemental analysis at a distance of 50 meters.

In this study, in order to enhance the intensity and sensitivity of the obtained spectra, a high-energy double-pulse laser was used in our experiments, and the spectral signals of Cd were significantly enhanced by optimizing the pulse interval, spectrograph delay, and integration time for the best matching parameter. To obtain accurate quantitative analysis results, feature spectral screening algorithms such as LAR, PCA, and SPA combined with PLS, SVM, ANN, and CNN models were tested to establish several quantitative analysis models to realize the accurate prediction of Cd elements in soil. The best correlation coefficient for the prediction set reached R2=97.75%.

In this work, the horizontal and vertical migration patterns of Cd in soil were revealed by the quantitative detection of Cd, which provides a reliable solution for the detection of cadmium pollution in soil at a long distance and large scale. This technique provides a valuable method for the detection of heavy metals in soil in areas with serious heavy metal pollution such as smelters and landfills.

Keywords
Remote LIBS;Soil pollution;Chemometrics;Cd profiling
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