1. Department of Electronic Information Engineering, College of Engineering, Shantou University, Shantou 515063, China
2. Department of Mechanical Engineering, College of Engineering, Shantou University, Shantou 515063, China
3. Institute of Geophysical and Geochemical Exploration, China Academy of Geological Sciences, Langfang 065000, China
4. Research Center of Geochemical Survey and Assessment on Land Quality, China Geological Survey, Langfang 065000, China
Abstract:Hyperspectral technology can provide nearly continuous spectral curves of ground objects, which has excellent potential for retrievingthe soil's components. This paper investigates components retrieval from contaminated soil by hyperspectral technology. By so doing, it analyzes thesoil cadmium (Cd) concentration measured in the laboratory and the corresponding hyperspectral curvature data obtained at the same period, following whichthe retrieval model for the soil Cd concentration from the hyperspectral data in light with the (Deep Forest 2021, DF21) model is developed. In this study, the original spectrum(OS) data and the data processed by the Principal Component Analysis (PCA) are used as the model's input parameters. Subsequently, two models, i.e., the OS-DF21 model based on the original spectral data and the PCA-DF21 model based on the PCA processed data, are established. The relationships between the input parameters and soil Cd concentration are respectively obtained by the OS-DF21 model and PCA-DF21 model. Then the soil Cd concentrationis estimated from the testing samples accordingly. To evaluate the retrieval performance, three indices, namely the coefficient of determination (R2), Root Mean Square Error (RMSE), and Residual Predictive Deviation (RPD) applied in this study. It is found that the OS-DF21 model has the best performance for the retrieval of soil Cd concentration, whose R2, RMSE, and RPD are 0.873, 0.120, and 2.892, respectively. In contrast, the PCA-DF21 model has arelatively lower retrieval accuracy, with R2, RMSE, and RPD being 0.779, 0.159, and 2.190, though the PCA can reduce the dimensionality of the spectral data. In this regard, the DF21 shows good retrieval performance and can be an essential supplementary method for soil heavy metal surveys in the study area and similar environmental regions.
Key words:Soil Cd concentration; DF21; Principal component analysis (PCA); Hyperspectral technology; Retrieval model
[1] Liao M, Xie X, Ma A, et al. Journal of Soils and Sediments, 2010, 10(5): 818.
[2] HU Qing-qing, NIE Chao-jia, SHEN Qiang, et al(胡青青,聂超甲,沈 强,等). Journal of Agro-Environment Science (农业环境科学学报), 2019, 38(3): 534.
[3] XU Xi-bo, ZHANG Sen-lin, BO Fan-sheng, et al(徐夕博,张森林,卜凡升,等). Journal of Henan Agricultural Sciences(河南农业科学), 2018, 47(7): 77.
[4] LEI Yu-bin, LIU Ning, GUO Yun-kai, et al(雷宇斌,刘 宁,郭云开,等). Engineering of Surveying and Mapping(测绘工程), 2018, 27(11): 71.
[5] LAN Miao, YANG Bin, SONG Qiang, et al(兰 淼,杨 斌,宋 强,等). Journal of Anhui Polytechnic University(安徽工程大学学报), 2021, 36(5): 47.
[6] LIU Hui-min, ZHEN Jia-qi, LIU Yong, et al(刘慧敏,甄佳奇,刘 勇,等). Journal of Chinese Agricultural Mechanization(中国农机化学报) , 2020, 41(9): 190.
[7] LU Zhi-hong, LIU Xin-yao, CHANG Shu-juan, et al(卢志宏,刘辛瑶,常书娟,等). Pratacultural Science(草业科学), 2018, 35(9): 2127.
[8] Zhou Z H, FENG J. Proceedings of the 26th International Joint Conference on Artificial Intelligence. Melbourne, Australia, AAAI Press,2017: 3553.
[9] He Yong, Song Haiyan, Pereira A G, et al. Journal of Zhejiang University SCIENCE, 2005,6(11): 1081.
[10] Ministry of Ecological Environment, State Administration for Market Regulatory(生态环境部、国家市场监督管理总局). National Standard of the People's Republic of China GB 15618—2018 Soil Environment Quality-Risk Control Standard for Soil Contamination of Agriculture Land [中华人民共和国国家标准(GB 15618—2018土壤环境质量农用地土壤污染风险管控标准(试行))], 2018.
[11] Liu F, Ting K, Yu Y, et al. Journal of Artificial Intelligence Research, 2008,(32): 355.
[12] GUO Fei, XU Zhen, MA Hong-hong, et al(郭 飞,许 镇,马宏宏,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2021, 41(5): 1625.