激光与光电子学进展, 2020, 57 (19): 192801, 网络出版: 2020-09-27   

基于土壤协变量与VIS-NIR光谱估算土壤有机质含量的研究 下载: 699次

Soil Organic Matter Content Estimation Based on Soil Covariate and VIS-NIR Spectroscopy
马国林 1,2,3丁建丽 1,2,3,*张子鹏 1,2,3
作者单位
1 新疆大学资源与环境科学学院, 新疆 乌鲁木齐 830046
2 新疆大学绿洲生态教育部重点实验室, 新疆 乌鲁木齐 830046
3 新疆大学智慧城市与环境建模自治区普通高校重点实验室, 新疆 乌鲁木齐 830046
引用该论文

马国林, 丁建丽, 张子鹏. 基于土壤协变量与VIS-NIR光谱估算土壤有机质含量的研究[J]. 激光与光电子学进展, 2020, 57(19): 192801.

Guolin Ma, Jianli Ding, Zipeng Zhang. Soil Organic Matter Content Estimation Based on Soil Covariate and VIS-NIR Spectroscopy[J]. Laser & Optoelectronics Progress, 2020, 57(19): 192801.

参考文献

[1] Alex M B, Damien J F, Andrea K. The dimensions of soil security[J]. Geoderma, 2014, 213: 203-213.

[2] Ding JL, Yu D L.Monitoring and evaluating spatial variability of soil salinity in dry and wet seasons in the Werigan-Kuqa Oasis, China, using remotesensing and electromagnetic induction instruments[J].Geoderma, 2014, 235/236: 316- 322.

[3] Gholizadeh A, Saberioon M, Ben-Dor E, et al. Monitoring of selected soil contaminants using proximal and remote sensing techniques: background, state-of-the-art and future perspectives[J]. Critical Reviews in Environmental Science and Technology, 2018, 48(3): 243-278.

[4] Chen T, Chang Q R. Clevers J G P W, et al. Rapid identification of soil cadmium pollution risk at regional scale based on visible and near-infrared spectroscopy[J]. Environmental Pollution, 2015, 206: 217-226.

[5] Gholizadeh A, Boruvka L, Saberioon M M, et al. Comparing different data preprocessing methods for monitoring soil heavy metals based on soil spectral features[J]. Soil and Water Research, 2016, 10(4): 218-227.

[6] Dorau K, Pohl L, Just C, et al. Soil organic matter and phosphate sorption on natural and synthetic Fe oxides under in situ conditions[J]. Environmental Science & Technology, 2019, 53(22): 13081-13087.

[7] 王丹, 田秀平, 张之一. 白浆土各形态Fe、Mn、Cu和Zn分布及其与有机质间的关系[J]. 天津农学院学报, 2016, 23(1): 14-17, 22.

    Wang D, Tian X P, Zhang Z Y. Distribution of various forms iron, manganese, copper, zinc and relationship between organic matter and various forms on lessive[J]. Journal of Tianjin Agricultural University, 2016, 23(1): 14-17, 22.

[8] Rietz D N, Haynes R J. Effects of irrigation-induced salinity and sodicity on soil microbial activity[J]. Soil Biology and Biochemistry, 2003, 35(6): 845-854.

[9] 王国栋, 褚贵新, 刘瑜, 等. 干旱绿洲长期微咸地下水灌溉对棉田土壤微生物量影响[J]. 农业工程学报, 2009, 25(11): 44-48.

    Wang G D, Chu G X, Liu Y, et al. Effects of long-term irrigation with brackish groundwater on soil microbial biomass in cotton field in arid oasis[J]. Transactions of the CSAE, 2009, 25(11): 44-48.

[10] Radim V, Radka K, Lubo B, et al. Combining reflectance spectroscopy and the digital elevation model for soil oxidizable carbon estimation[J]. Geoderma, 2017, 303: 133-142.

[11] Fernandes M M H, Coelho A P, Fernandes C, et al. Estimation of soil organic matter content by modeling with artificial neural networks[J]. Geoderma, 2019, 350: 46-51.

[12] Kweon G, Lund E, Maxton C. Soil organic matter and cation-exchange capacity sensing with on-the-go electrical conductivity and optical sensors[J]. Geoderma, 2013, 199: 80-89.

[13] Siebielec G. McCarty G W, Stuczynski T I, et al. Near- and mid-infrared diffuse reflectance spectroscopy for measuring soil metal content[J]. Journal of Environmental Quality, 2004, 33(6): 2056-2069.

[14] 于雷, 洪永胜, 周勇, 等. 高光谱估算土壤有机质含量的波长变量筛选方法[J]. 农业工程学报, 2016, 32(13): 95-102.

    Yu L, Hong Y S, Zhou Y, et al. Wavelength variable selection methods for estimation of soil organic matter content using hyperspectral technique[J]. Transactions of the CSAE, 2016, 32(13): 95-102.

[15] 田美玲, 葛翔宇, 丁建丽, 等. 耦合机器学习和机载高光谱数据的土壤含水量估算[J]. 激光与光电子学进展, 2020, 57(9): 093002.

    Tian M L, Ge X Y, Ding J L, et al. Coupled machine learning and unmanned aerial vehicle based hyperspectral data for soil moisture content estimation[J]. Laser & Optoelectronics Progress, 2020, 57(9): 093002.

[16] Cheng H, Shen R L, Chen Y Y, et al. Estimating heavy metal concentrations in suburban soils with reflectance spectroscopy[J]. Geoderma, 2019, 336: 59-67.

[17] van der Meer F. Acknowledgement of reviewer services to the International Journal Applied Earth Observation and Geoinformation[J]. International Journal of Applied Earth Observation and Geoinformation, 2017, 58: A1.

[18] 陈斌, 邹贤勇, 朱文静. PCA结合马氏距离法剔除近红外异常样品[J]. 江苏大学学报(自然科学版), 2008, 29(4): 277-279, 292.

    Chen B, Zou X Y, Zhu W J. Eliminating outlier samples in near-infrared model by method of PCA-mahalanobis distance[J]. Journal of Jiangsu University (Natural Science Edition), 2008, 29(4): 277-279, 292.

[19] 葛翔宇, 丁建丽, 王敬哲, 等. 基于竞争适应重加权采样算法耦合机器学习的土壤含水量估算[J]. 光学学报, 2018, 38(10): 1030001.

    Ge X Y, Ding J L, Wang J Z, et al. Estimation of soil moisture content based on competitive adaptive reweighted sampling algorithm coupled with machine learning[J]. Acta Optica Sinica, 2018, 38(10): 1030001.

[20] Savitzky A. Golay M J E. Smoothing and differentiation of data by simplified least squares procedures[J]. Analytical Chemistry, 1964, 36(8): 1627-1639.

[21] Isaksson T, Næs T. The effect of multiplicative scatter correction (MSC) and linearity improvement in NIR spectroscopy[J]. Applied Spectroscopy, 1988, 42(7): 1273-1284.

[22] Viscarra Rossel R A, Behrens T, Ben-Dor E, et al. A global spectral library to characterize the world's soil[J]. Earth-Science Reviews, 2016, 155: 198-230.

[23] 张子鹏, 丁建丽, 王敬哲. 基于谐波分析算法的干旱区绿洲土壤光谱特性研究[J]. 光学学报, 2019, 39(2): 0228003.

    Zhang Z P, Ding J L, Wang J Z. Spectral characteristics of oasis soil in arid area based on harmonic analysis algorithm[J]. Acta Optica Sinica, 2019, 39(2): 0228003.

[24] Weng Y L, Gong P, Zhu Z L. A spectral index for estimating soil salinity in the Yellow River Delta region of China using EO-1 Hyperion data[J]. Pedosphere, 2010, 20(3): 378-388.

[25] Wold S, Sjöström M, Eriksson L. PLS-regression: a basic tool of chemometrics[J]. Chemometrics and Intelligent Laboratory Systems, 2001, 58(2): 109-130.

[26] 薛利红, 周鼎浩, 李颖, 等. 不同利用方式下土壤有机质和全磷的可见近红外高光谱反演[J]. 土壤学报, 2014, 51(5): 993-1002.

    Xue L H, Zhou D H, Li Y, et al. Prediction of soil organic matter and total phosphorus with VIS-NIR hyperspectral inversion relative to land use[J]. Acta Pedologica Sinica, 2014, 51(5): 993-1002.

[27] EhrentrautD, PollnauM. On the potential of BaSO4∶Mn 6+ for broadly tunable laser emission in the near infrared spectral region [C]∥Conference on Lasers and Electro-Optics Europe, June 22-27, 2003, Munich, Germany. New York: IEEE, 2003: 343.

[28] Hong Y S, Shen R L, Cheng H, et al. Cadmium concentration estimation in peri-urban agricultural soils: Using reflectance spectroscopy, soil auxiliary information, or a combination of both?[J]. Geoderma, 2019, 354: 113875.

[29] Hong Y S, Liu Y L, Chen Y Y, et al. Application of fractional-order derivative in the quantitative estimation of soil organic matter content through visible and near-infrared spectroscopy[J]. Geoderma, 2019, 337: 758-769.

[30] 姜雪芹, 叶勤, 林怡, 等. 基于谐波分析和高光谱遥感的土壤含水量反演研究[J]. 光学学报, 2017, 37(10): 1028001.

    Jiang X Q, Ye Q, Lin Y, et al. Inverting study on soil water content based on harmonic analysis and hyperspectral remote sensing[J]. Acta Optica Sinica, 2017, 37(10): 1028001.

[31] 叶勤, 姜雪芹, 李西灿, 等. 基于高光谱数据的土壤有机质含量反演模型比较[J]. 农业机械学报, 2017, 48(3): 164-172.

    Ye Q, Jiang X Q, Li X C, et al. Comparison on inversion model of soil organic matter content based on hyperspectral data[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(3): 164-172.

[32] 沈兰芝, 高懋芳, 闫敬文, 等. 基于SVR和PLSR的土壤有机质高光谱估测模型研究[J]. 中国农业信息, 2019( 1): 58- 71.

    Shen LZ, Gao MF, Yan JW, et al. Estimation model of soil organic matter based on SVR and PLSR[J]. China Agricultural Informatics, 2019( 1): 58- 71.

[33] 李冠稳, 高小红, 肖能文, 等. 特征变量选择和回归方法相结合的土壤有机质含量估算[J]. 光学学报, 2019, 39(9): 0930002.

    Li G W, Gao X H, Xiao N W, et al. Estimation of soil organic matter content based on characteristic variable selection and regression methods[J]. Acta Optica Sinica, 2019, 39(9): 0930002.

[34] Rossel R A V, Behrens T. Using data mining to model and interpret soil diffuse reflectance spectra[J]. Geoderma, 2010, 158(1/2): 46-54.

[35] HortaA, MaloneB, StockmannU, et al. and spatial analysis for enhanced assessment of soil contamination: a prospective review[J]. Geoderma, 2015, 241/242: 180- 209.

[36] 赵启东, 葛翔宇, 丁建丽, 等. 结合分数阶微分技术与机器学习算法的土壤有机碳含量光谱估测[J]. 激光与光电子学进展, 2020, 57(15): 153001.

    Zhao Q D, Ge X Y, Ding J L, et al. Combination of fractional order derivative and machine learning algorithms for the spectral estimation of soil organic carbon content[J]. Laser & Optoelectronics Progress, 2020, 57(15): 153001.

[37] Chakraborty S, Man T, Paulette L, et al. Rapid assessment of smelter/mining soil contamination via portable X-ray fluorescence spectrometry and indicator kriging[J]. Geoderma, 2017, 306: 108-119.

[38] O"Rourke S M, Stockmann U, Holden N M, et al. An assessment of model averaging to improve predictive power of portable VIS-NIR and XRF for the determination of agronomic soil properties[J]. Geoderma, 2016, 279: 31-44.

马国林, 丁建丽, 张子鹏. 基于土壤协变量与VIS-NIR光谱估算土壤有机质含量的研究[J]. 激光与光电子学进展, 2020, 57(19): 192801. Guolin Ma, Jianli Ding, Zipeng Zhang. Soil Organic Matter Content Estimation Based on Soil Covariate and VIS-NIR Spectroscopy[J]. Laser & Optoelectronics Progress, 2020, 57(19): 192801.

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