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- 2016
利用区域土壤光谱库研究土壤有机碳反演模型传递性
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Abstract:
土壤有机碳的有效评估对全球碳循环和农业可持续发展具有重要作用。可见光-近红外光谱技术已广泛用于土壤有机碳含量的反演研究。然而,基于可见光-近红外光谱的土壤有机碳反演模型通常具有一定的区域局限性。本文基于湖北钟祥市和洪湖市两个区域的土壤光谱和有机碳量测数据(样本数分别为100和96),探究土壤有机碳反演模型在不同区域间的传递性。结果表明,钟祥市或洪湖市区域模型都不能用于另一个区域,但基于钟祥样本全集与洪湖区域30个土壤样本数据建立的模型对洪湖区域土壤有机碳含量有很好的预测效果(R2=0.88, RMSE=2.51 g·kg-1)。尽管模型在不同区域间的传递性非常有限,但将少量目标区域样本添加到现有区域土壤光谱库中所建立的偏最小二乘回归模型能够估算目标区域土壤有机碳的含量,降低目标区域的采样和量测成本
| [1] | He Ting, Wang Jing, Lin Zongjian, et al. Spectral Features of Soil Organic Matter[J]. <em>Geometics and Information Science of Wuhan University</em>, 2006, 31(11): 975-979(何挺, 王静, 林宗坚, 等, 土壤有机质光谱特征研究[J]. 武汉大学学报·信息科学版, 2006, 31(11): 975-979) |
| [2] | Liu Gang, Shen Shouyun, Yan Wende, et al. Characteristics of Organic Carbon and Nutrient Content in Five Soil Types in Honghu Wetland Ecosystems[J]. <em>Acta Ecologica Sinica</em>, 2011,24:7 625-7 631(刘刚, 沈守云, 闫文德, 等. 洪湖湿地生态系统土壤有机碳及养分含量特征 [J]. 生态学报, 2011, 24: 7 625-7 631) |
| [3] | Barnes E M, Sudduth K A, Hummel J W, et al. Remote and Ground-Based Sensor Techniques to Map Soil Properties[J]. <em>Photogrammetric Engineering and Remote Sensing,</em> 2003,69: 619-630 |
| [4] | Zhou Qing, Zhou Bin,Wang Renchao, et al. Effect of Geometric Conditions on Soil Hyperspectral Data Scatter Characteristic in Laboratory Test[J]. <em>Journal of South China Agricultural University</em>, 2005,26(1): 31-35 (周清, 周斌, 王人潮, 等. 室内几何测试条件对土壤高光谱数据离散性的影响 [J]. 华南农业大学学报, 2005, 26(1): 31-35) |
| [5] | Honorato F A, Galvao R K H, Pimentel M F, et al. Robust Modeling for Multivariate Calibration Transfer by the Successive Projections Algorithm[J]. <em>Chemometrics and Intelligent Laboratory Systems</em>, 2005, 76(1): 65-72 |
| [6] | Brown D J, Shepherd K D, Walsh M G, et al. Global Soil Characterization with VNIR Diffuse Reflectance Spectroscopy [J]. <em>Geoderma</em>, 2006, 132(3/4): 273-290 |
| [7] | Peng Xiaoting, Gao Wenxiu, Wang Junjie. Inversion of Soil Parameters from Hyperspectra Based on Continuum Removal and Partial Least Squares Regression[J]. <em>Geometics and Information Science of Wuhan University</em>, 2014,39(7):862-866(彭小婷, 高文秀, 王俊杰. 基于包络线去除和偏最小二乘的土壤参数光谱反演[J]. 武汉大学学报·信息科学版, 2014,39(7):862-866) |
| [8] | Shi Zhou, Guo Yan, Jin Xi, et al. Advance Mentin Study on Proximal Soil Sensing[J]. <em>Acta Pedologica Sinica</em>, 2011(6):1 274-1 281(史舟, 郭燕, 金希,等. 土壤近地传感器研究进展 [J]. 土壤学报, 2011(6): 1 274-1 281) |
| [9] | Lu Mingxing, Xu Hui, He Liyuan, et al. The Spatial and Temporal Changes of the Farmland Soil Fertilities in the Zhongxiang City, Hubei Province[J]. <em>Journal of Huazhong Agricultural University</em>, 2009,28(4):431-437(鲁明星, 徐辉, 贺立源,等. 湖北省钟祥市耕地土壤养分时空变化分析 [J]. 华中农业大学学报, 2009,28(4): 431-437) |
| [10] | Galvao R K H, Araujo M C U, José G E, et al. A Method for Calibration and Validation Subset Partitioning[J]. <em>Talanta</em>, 2005, 67(4): 736-740 |
| [11] | Vasques G M S, Grunwald J O, Sickman. Comparison of Multivariate Methods for Inferential Modeling of Soil Carbon Using Visible/Near-infrared Spectra[J]. <em>Geoderma</em>, 2008, 146(1/2): 14-25 |
| [12] | Wise B, Gallagher N, Bro R,et al. PLS_Toolbox for Use with MATLAB, Version 5.5.1[R]. Eigenvector Research, Inc,Wenatchee, USA,2009 |
| [13] | Viscarra Rossel R A , Jeon Y S, Odeh I O A, et al. Using a Legacy Soil Sample to Develop a Mid-IR Spectral Library[J]. <em>Soil Research</em>, 2008, 46(1): 1-16 |
| [14] | Brown D J. Using a Global VNIR Soil-spectral Library for Local Soil Characterization and Landscape Modeling in a 2nd-order Uganda Watershed[J]. <em>Geoderma</em>, 2007, 140(4): 444-453 |
| [15] | Brown D J, Bricklemyer R S, Miller R. Validation Requirements for Diffuse Reflectance Soil Characterization Models With a Case Study of VNIR Soil C Prediction in Montana[J]. <em>Geoderma</em>, 2005, 129(3): 251-267 |
| [16] | Brunet D, Barthès B G, Chotte J L, et al. Determination of Carbon and Nitrogen Contents in Alfisols, Oxisols and Ultisols from Africa and Brazil Using NIRS Analysis: Effects of Sample Grinding and Set Heterogeneity[J]. <em>Geoderma</em>, 2007, 139(1/2): 106-117 |
| [17] | Esbensen K, Guyot D, Westad F, et al. Multivariate Data Analysis-in Practice: An Introduction to Multivariate Data Analysis and Experimental Design[M]. Osto, Norway: CAMO Press, 2001 |
| [18] | Chang C W, Laird D A. Near-infrared Reflectance Spectroscopic Analysis of Soil <em>C</em> and <em>N</em>[J]. <em>Soil Science</em>, 2002, 167(2): 110-116 |
| [19] | Sankey J B, Brown D J, Bernard M L, et al. Comparing Local vs. Global Visible and Near-infrared (VisNIR) Diffuse Reflectance Spectroscopy (DRS) Calibrations for the Prediction of Soil Clay, Organic C and Inorganic C[J]. <em>Geoderma</em>, 2008, 148(2): 149-158 |
| [20] | Ji Wenjun, Shi Zhou, Zhou Qing, et al. VIS-NIR Reflectance Spectroscopy of the Organic Matterin Several Types of Soils[J]. <em>J Infrared Millim Waves</em>,2012, 31(3):277-282 (纪文君, 史舟, 周清, 等. 几种不同类型土壤的VIS-NIR光谱特性及有机质响应波段 [J]. 红外与毫米波学报, 2012, 31(3): 277-282) |
