地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (8): 1123-1132.doi: 10.3724/SP.J.1047.2016.01123
乔星星(), 冯美臣*(
), 杨武德, 孙慧, 郭小丽, 史超超
收稿日期:
2015-12-07
修回日期:
2016-02-17
出版日期:
2016-08-10
发布日期:
2016-08-10
通讯作者:
冯美臣
E-mail:qxx1702@163.com;fmc101@163.com
作者简介:
作者简介:乔星星(1989-),女,山西长子人,硕士生,研究方向为作物生态和信息技术。E-mail:
基金资助:
QIAO Xingxing(), FENG Meichen*(
), YANG Wude, SUN Hui, GUO Xiaoli, SHI Chaochao
Received:
2015-12-07
Revised:
2016-02-17
Online:
2016-08-10
Published:
2016-08-10
Contact:
FENG Meichen
E-mail:qxx1702@163.com;fmc101@163.com
摘要:
光谱数据变换对消除背景、噪音影响以及提取光谱特征有重要的作用,是光谱数据分析过程中的必要步骤。为了研究光谱变换处理对土壤氮素PLSR模型的影响精度,并选择最佳光谱变换处理方法,本文对原始光谱数据进行了15种典型光谱变换,通过比较不同变换光谱与土壤氮素的相关性,实现土壤氮素的PLSR精确诊断,并综合评定最佳光谱数据变换方法。结果表明,涉及微分处理后的光谱变换,尤其是先进行开方(T8、T11)、对数(T6、T12)等变换后再进行微分处理,可提高其与土壤氮素的相关性。在引入较少因子变量个数的条件下,该方法使因变量解释量达到了98%。综合考虑模型的校正、验证效果及模型复杂度(模型最佳因子变量个数),可得出光谱平方根的一阶微分变换处理(T8)为最佳的土壤光谱变换算法。该条件下的土壤氮素的校正模型表现为R2=0.985、RMSEC=0.000132、Fn=6,验证模型的表现为R2=0.9853、RMSEV=0.000162,结果表明基于T8的光谱数据变换可实现本试验条件下土壤氮素的光谱估算。另外,可以考虑将原始光谱的一阶微分(T9)、对数和对数倒数的一阶微分(T6、T7)以及平方根和对数的二阶微分(T11、T12)作为光谱数据变换方法。本文研究结果可为土壤氮素估算和光谱数据预处理提供技术参考。
乔星星, 冯美臣, 杨武德, 孙慧, 郭小丽, 史超超. 变换光谱数据对土壤氮素PLSR模型的影响研究[J]. 地球信息科学学报, 2016, 18(8): 1123-1132.DOI:10.3724/SP.J.1047.2016.01123
QIAO Xingxing,FENG Meichen,YANG Wude,SUN Hui,GUO Xiaoli,SHI Chaochao. Effect of Spectral Transformation Processes on the PLSR Models of Soil Nitrogen[J]. Journal of Geo-information Science, 2016, 18(8): 1123-1132.DOI:10.3724/SP.J.1047.2016.01123
表3
基于不同变换光谱的PLSR土壤氮素模型的校正和验证参数统计"
变换算法 | 校正模型参数 | 验证模型参数 | 最优因子个数 | ||
---|---|---|---|---|---|
R2 | RMSEC | R2 | RMSEV | ||
T0 | 0.969192 | 0.000270 | 0.9843 | 0.000170 | 17 |
T1 | 0.955778 | 0.000390 | 0.9825 | 0.000200 | 25 |
T2 | 0.983095 | 0.000149 | 0.9927 | 0.000082 | 17 |
T3 | 0.984178 | 0.000139 | 0.9888 | 0.000112 | 18 |
T4 | 0.986729 | 0.000116 | 0.9933 | 0.000076 | 14 |
T5 | 0.967169 | 0.000290 | 0.9789 | 0.000224 | 23 |
T6 | 0.982890 | 0.000150 | 0.9897 | 0.000114 | 10 |
T7 | 0.981017 | 0.000166 | 0.9858 | 0.000159 | 10 |
T8 | 0.985022 | 0.000132 | 0.9853 | 0.000162 | 6 |
T9 | 0.981608 | 0.000016 | 0.9865 | 0.000143 | 10 |
T10 | 0.981803 | 0.000159 | 0.9886 | 0.000131 | 12 |
T11 | 0.977755 | 0.000195 | 0.9709 | 0.000313 | 5 |
T12 | 0.985058 | 0.000130 | 0.9848 | 0.000162 | 9 |
T13 | 0.983277 | 0.000145 | 0.9865 | 0.000154 | 14 |
T14 | 0.985637 | 0.000126 | 0.9903 | 0.000107 | 17 |
T15 | 0.977619 | 0.000196 | 0.9900 | 0.000107 | 16 |
[1] |
Zhao S C, Qiu S J, Cao C Y, et al.Responses of soil properties, microbial community and crop yields to various rates of nitrogen fertilization in a wheat-maize cropping system in north-central China[J]. Agriculture, Ecosystems and Environment, 2014,194:29-37.
doi: 10.1016/j.agee.2014.05.006 |
[2] |
Gnyp M L, Miao Y X, Yuan F, et al.Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages[J]. Field Crops Research, 2014,155:42-55.
doi: 10.1016/j.fcr.2013.09.023 |
[3] |
张春桂,张星,陈敏艳,等.福建近岸海域悬浮泥沙浓度遥感定量监测研究[J].自然资源学报,2008,23(1):150-160.
doi: 10.11849/zrzyxb.2008.01.017 |
[ Zhang C G, Zhang X, Chen M Y, et al.Study on remote sensing quantitative model of suspended sediments in the coastal waters of Fujian[J]. Journal of Natural Resources, 2008,23(1):150-160. ]
doi: 10.11849/zrzyxb.2008.01.017 |
|
[4] |
An X F, Li M Z, Zheng L H, et al.Eliminating the interference of soil moisture and particle size on predicting soil total nitrogen content using a NIRS-based portable detector[J]. Computers and Electronics in Agriculture, 2015,112:47-53.
doi: 10.1016/j.compag.2014.11.003 |
[5] | 张娟娟. 土壤养分信息的光谱估测研究[D].南京:南京农业大学,2009. |
[ Zhang J J.Estimating soil nutrient information based on spectral analysis technology[D]. Nanjing: Nanjing Agricultural University, 2009. ] | |
[6] | Stenberg B, Rossel R A V, Mouazen A M, et al. Visible and near infrared spectroscopy in soil science[M]. Burlington: Academic Press, 2010. |
[7] | 王磊,白由路,卢艳丽,等.光谱数据变换对玉米氮素含量反演精度的影响[J].遥感技术与应用,2011,26(2):220-225. |
[ Wang L, Bai Y L, Lu Y L, et al.Effect on retrieval precision for corn N content by spectrum data transformation[J]. Remote Sensing Technology and Application, 2011,26(2):220-225. ] | |
[8] | Mashimbye Z E, Cho M A, Nell J P, et al.Model-based integrated methods for quantitative estimation of soil salinity from hyperspectral remote sensing data: a case study of selected South African soils[J]. Pedosphere, 2012,22(5):640-649. |
[9] | 贺军亮,蒋建军,周生路,等.土壤有机质含量的高光谱特性及其反演[J].中国农业科学,2007,40(3):638-643. |
[ He J L, Jiang J J, Zhou S L, et al.The hyperspectral characteristics and retrieval of soil organic matter content[J]. Scientia Agricultura Sinica, 2007,40(3):638-643. ] | |
[10] |
Stevens A, Udelhoven T, Denis A, et al.Measuring soil organic carbon in croplands at regional scale using air borne imaging spectroscopy[J]. Geoderma, 2010,158(1):32-45.
doi: 10.1016/j.geoderma.2009.11.032 |
[11] |
Tian Y, Zhang J, Yao X, et al. Laboratory assessment of three quantitative methods for estimating the organic matter content of soils in China based on visible/near-infrared reflectance spectra[J]. Geoderma, 2013,202-203:161-170.
doi: 10.1016/j.geoderma.2013.03.018 |
[12] |
Kemper T, Sommer S.Estimate of heavy metal contamination in soils after a mining accident using reflectance spectroscopy[J]. Environmental Science & Technology, 2002,36(12):2742-2747.
doi: 10.1021/es015747j pmid: 12099473 |
[13] |
Nawar S, Buddenbaum H, Hill J, et al.Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy[J]. Soil & Tillage Research, 2016,155:510-522.
doi: 10.1016/j.still.2015.07.021 |
[14] |
Bayer A, Bachmann M, Müller A, et al.A comparison of feature-based MLR and PLS regression techniques for the prediction of three soil constituents in a degraded South African ecosystem[J]. Applied and Environmental Soil Science, 2012:971252.
doi: 10.1155/2012/971252 |
[15] | Feng Y, Li X, Xu K, et al.Qualitative and simultaneous quantitative analysis of cimetidine polymorphs by ultraviolet-visible and shortwave near-infrared diffuse reflectance spectroscopy and multivariate calibration models[J]. Journal of Pharmaceutical and Biomedical Analysis, 2015,104:112-121. |
[16] |
Mohanty B, Gupta A, Das B S.Estimation of weathering indices using spectral reflectance over visible to mid-infrared region[J]. Geoderma, 2016,266:111-119.
doi: 10.1016/j.geoderma.2015.11.030 |
[17] |
Yu X, Liu Q, Wang Y, et al.Evaluation of MLSR and PLSR for estimating soil element contents using visible/near-infrared spectroscopy in apple orchards on the Jiaodong peninsula[J]. Catena, 2016,137:340-349.
doi: 10.1016/j.catena.2015.09.024 |
[18] | 鲁如坤. 土壤农业化学分析方法[M].北京:中国农业科技出版社,2000. |
[ Lu R K.Soil agricultural chemical analysis method[M]. Beijing: China's Agricultural Science and Technology Publishing, 2000. ] | |
[19] | Wold S.PLS for multivariate linear modeling[J]. Chemometric Methods in Molecular Design, 1995,2:195. |
[20] |
Chang C W, Laird D A.Near-infrared reflectance spectroscopic analysis of soil C and N[J]. Soil Science, 2002,167(2):110-116.
doi: 10.1097/00010694-200202000-00003 |
[21] | 周锦. 土壤中氮含量的测定分析[J].农业科技与信息,2008,15:40-41. |
[ Zhou J.Determination and analysis fornitrogen content in soil[J]. Information of Agricultural Science and Technology, 2008,15:40-41. ] | |
[22] | 卢艳丽,白由路,王磊,等.黑土土壤中全氮含量的高光谱预测分析[J].农业工程学报,2010,26(1):256-261. |
[ Lu Y L, Bai Y L, Wang L, et al.Determination for total nitrogen content in black soil using hyperspectral data[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2010,26(1):256-261. ] | |
[23] |
沈润平,丁国香,魏国栓,等.基于人工神经网络的土壤有机质含量高光谱反演[J].土壤学报,2009,46(3):391-397.
doi: 10.3321/j.issn:0564-3929.2009.03.003 |
[ Shen R P, Ding G X, Wei G S, et al.Retrieval of soil organic matter content from hyper-spectrum based on ANN[J]. Acta Pedologica Sinica, 2009,46(3):391-397. ]
doi: 10.3321/j.issn:0564-3929.2009.03.003 |
|
[24] | 杨爱霞,丁建丽.新疆艾比湖湿地土壤有机碳含量的光谱测定方法对比[J].农业工程学报,2015,31(18):162-168. |
[ Yang A X, Ding J L.Comparative assessment of two methods for estimation of soil organic carbon content by Vis-NIR spectra in Xinjiang Ebinur Lake Wetland[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015,31(18):162-168. ] | |
[25] |
Zornoza R, Guerrero C, Mataix-Solera J, et al.Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils[J]. Soil Biology and Biochemistry, 2008,40(7):1923-1930.
doi: 10.1016/j.soilbio.2008.04.003 |
[26] |
Anderson K, Croft H.Remote sensing of soil surface properties[J]. Progress in Physical Geography, 2009,33(4):457-473.
doi: 10.1177/0309133309346644 |
[27] |
王镇浦,周国华,罗国安.偏最小二乘法(PLS)及其在分析化学中的应用[J].分析化学,1989,17(7):662-669.
doi: 10.1007/BF02943117 |
[ Wang Z P, Zhou G H, Luo G A.Partial least squares method (PLS) and its application in analytical chemistry[J]. Analytical Chemistry, 1989,17(7):662-669. ]
doi: 10.1007/BF02943117 |
|
[28] |
Wold S, Sjöström M, Eriksson L.PLS-regression: a basic tool of chemometrics[J]. Chemometrics and Intelligent Laboratory Systems, 2001,58(2):109-130.
doi: 10.1016/S0169-7439(01)00155-1 |
[29] |
Wang Q, Yi Q X, Bao A M, et al.Estimating chlorophyll density of cotton canopy by hyperspectral reflectance[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2012,28(15):125-132.
doi: 10.3969/j.issn.1002-6819.2012.15.020 |
[30] |
Brown D J, Shepherd, K D, Walsh M G, et al. Global soil characterization with VNIR diffuse reflectance spectroscopy[J]. Geoderma, 2006,132(3):273-290.
doi: 10.1016/j.geoderma.2005.04.025 |
[31] | 司海青,姚艳敏,王德营,等.含水率对土壤有机质含量高光谱估算的影响[J].农业工程学报,2015,31(9):114-120. |
[ Si H Q, Yao Y M, Wang D Y, et al.Hyperspectral prediction of soil organic matter contents under different soil moisture contents[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2015,31(9):114-120. ] |
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