基于优化光谱指数的土壤有机质含量估算
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摘要
为了寻求估算土壤有机质含量的最佳光谱参数,实现土壤养分无损监测,使用ASD Field-Spec3型高光谱仪对野外采集的土壤样品进行室内光谱测定,并通过重铬酸钾氧化容量法测定土壤样品有机质质量比;利用两波段优化算法对构建的新算法(SOMCI/ND)进行波段优化,筛选基于不同光谱数据(原始光谱反射率及其对应的4种数学变换)运算下的最敏感波段组合,从而建立土壤有机质质量比高光谱估算模型。结果表明:通过归一化光谱指数(IND)和概念指数(ICI)比值构建的新算法(SOMCI/ND)优化后与土壤有机质质量比之间的相关性显著提高,在光谱原始数据及其平方根、倒数变换形式下,相关系数绝对值达到0. 82,且敏感的组合波段集中在2 220~2 240 nm和2 160~2 195 nm。基于平方根波段优化的估算模型效果最佳,估算精度R2P为0. 84,RMSEP为2. 24 g/kg,RPD为2. 89。对光谱数据的适当数学变换有利于优化光谱指数,更好地估算土壤有机质质量比,进一步实现土壤有机质质量比的高精度动态监测。
The rapid monitoring of soil organic matter content based on hyperspectral data is of great significance for evaluating soil fertility. The best spectral parameters for predicting soil organic matter content were tried to find and non-destructive monitoring of soil nutrients was achieved. ASD Field-Spec3 spectrometer was used to measure the indoor spectra of soil samples collected in the field,and the organic matter content of soil samples was measured by the potassium dichromate oxidation capacity method; the nitrogen planar component index(SOMCI/ND) was optimized by two-band optimization algorithm. Band optimization,screening the most sensitive spectral parameters of different spectral data(the original spectral reflectance and its corresponding four mathematical transformations), thus establishing a hyperspectral estimation model of soil organic matter content. The results showed that the correlations between soil organic matter content and the new algorithm(SOMCI/ND) optimized by the normalized spectral index(IND) and conceptual index(ICI) ratios were significantly improved. The raw data in the spectrum and its square root and reciprocal transformation form,the absolute value of correlation coefficient reached 0. 82,and the sensitive combination bands were concentrated in 2 220 ~ 2 240 nm and2 160 ~ 2 195 nm. The prediction model based on the square root band optimization had the best effect.The prediction accuracy was R2 Pof 0. 84,RMSEP of 2. 24 g/kg and RPD of 2. 89. Therefore,the appropriate mathematical transformation of the spectral data was conducive to optimizing the spectral index to better estimate the soil organic matter content,and further achieve high-precision dynamic monitoring of soil organic matter.
The rapid monitoring of soil organic matter content based on hyperspectral data is of great significance for evaluating soil fertility. The best spectral parameters for predicting soil organic matter content were tried to find and non-destructive monitoring of soil nutrients was achieved. ASD Field-Spec3 spectrometer was used to measure the indoor spectra of soil samples collected in the field,and the organic matter content of soil samples was measured by the potassium dichromate oxidation capacity method; the nitrogen planar component index(SOMCI/ND) was optimized by two-band optimization algorithm. Band optimization,screening the most sensitive spectral parameters of different spectral data(the original spectral reflectance and its corresponding four mathematical transformations), thus establishing a hyperspectral estimation model of soil organic matter content. The results showed that the correlations between soil organic matter content and the new algorithm(SOMCI/ND) optimized by the normalized spectral index(IND) and conceptual index(ICI) ratios were significantly improved. The raw data in the spectrum and its square root and reciprocal transformation form,the absolute value of correlation coefficient reached 0. 82,and the sensitive combination bands were concentrated in 2 220 ~ 2 240 nm and2 160 ~ 2 195 nm. The prediction model based on the square root band optimization had the best effect.The prediction accuracy was R2 Pof 0. 84,RMSEP of 2. 24 g/kg and RPD of 2. 89. Therefore,the appropriate mathematical transformation of the spectral data was conducive to optimizing the spectral index to better estimate the soil organic matter content,and further achieve high-precision dynamic monitoring of soil organic matter.
引文
1方少文,杨梅花,赵小敏,等.红壤区土壤有机质光谱特征与定量估算:以江西省吉安县为例[J].土壤学报,2014,51(5):1003-1010.FANG Shaowen,YANG Meihua,ZHAO Xiaomin,et al.Spectral characteristics and quantitative estimation of SOM in red soil typical of Ji'an county,Jiangxi province[J].Acta Pedologica Sinica,2014,51(5):1003-1010.(in Chinese)
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3田永超,张娟娟,姚霞,等.基于近红外光声光谱的土壤有机质含量定量建模方法[J].农业工程学报,2012,28(1):145-152.TIAN Yongchao,ZHANG Juanjuan,YAO Xia,et al.Quantitative modeling method of soil organic matter content based on nearinfrared photoacoustic spectroscopy[J].Transactions of the CSAE,2012,28(1):145-152.(in Chinese)
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5李美清,李晋阳.基于反射光谱特性的土壤有机质含量测定仪改进设计[J].农业机械学报,2008,39(10):148-151.LI Meiqing,LI Jinyang.Improved research on intellectual system for measuring soil organic matter content with spectrum method[J].Transactions of the Chinese Society for Agricultural Machinery,2008,39(10):148-151.(in Chinese)
6 KOOISTRA L,WANDERS J,EPEMA G F,et al.The potential of field spectroscopy for the assessment of sediment properties in river floodplains[J].Analytica Chimica Acta,2003,484(2):189-200.
7 KRISHNAN P,ALEXANDER J D,BUTLER B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Science Society of America Journal,1980,44(6):1282-1285.
8王延仓,杨贵军,朱金山,等.基于小波变换与偏最小二乘耦合模型估测北方潮土有机质含量[J].光谱学与光谱分析,2014,34(7):1922-1926.WANG Yancang,YANG Guijun,ZHU Jinshan,et al.Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares[J].Spectroscopy and Spectral Analysis,2014,34(7):1922-1926.(in Chinese)
9徐明星,周生路,丁卫,等.苏北沿海滩涂地区土壤有机质含量的高光谱估算[J].农业工程学报,2011,27(2):219-223.XU Mingxing,ZHOU Shenglu,DING Wei,et al.Hyperspectral reflectance models for predicting soil organic matter content in coastal tidal land area,northern Jiangsu[J].Transactions of the CSAE,2011,27(2):219-223.(in Chinese)
10 HUMMEL J W,SUDDUTH K A,HOLLINGER S E.Soil moisture and organic matter prediction of surface and subsurface soils using an NIR soil sensor[J].Computers and Electronics in Agriculture,2001,32(2):149-165.
11 CONFORTI M,BUTTAFUOCO G,LEONE A P,et al.Studying the relationship between water-induced soil erosion and soil organic matter using vis-NIR spectroscopy and geomorphological analysis:a case study in southern Italy[J].Catena,2013,110:44-58.
12 NOWKANDEH S M,HOMAEE M,NOROOZI A A.Mapping soil organic matter using hyperion images[J].International Journal of Agronomy&Plant Production,2013,4:1753-1759.
13栾福明,张小雷,熊黑钢,等.基于不同模型的土壤有机质含量高光谱反演比较分析[J].光谱学与光谱分析,2013,33(1):196-200.LUAN Fuming,ZHANG Xiaolei,XIONG Heigang,et al.Comparative analysis of soil organic matter content based on different hyperspectral inversion models[J].Spectroscopy and Spectral Analysis,2013,33(1):196-200.(in Chinese)
14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/OL].农业机械学报,2017,48(3):164-172.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?file_no=20170321&flag=1&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.03.021.YE Qin,JIANG Xueqin,LI Xican,et al.Comparison on inversion model of soil organic matter content based on hyperspectral data[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(3):164-172.(in Chinese)
15张小禹.乌鲁木齐市蔬菜基地土壤有效态镍的空间变异特征[J].新疆环境保护,2012,34(3):41-45.ZHANG Xiaoyu.Spatial variation characteristic of soil active nickel in Urumqi Vegetable Base[J].Environmental Protection of Xinjiang,2012,34(3):41-45.(in Chinese)
16王灵,朱建雯,钱翌,等.乌鲁木齐市菜地土壤和蔬菜铅含量及风险评价[J].新疆农业大学学报,2008,31(1):46-50.WANG Ling,ZHU Jianwen,QINA Yi,et al.Lead content in vegetable and soil of vegetable plot in Urumqi City and its risk evaluation[J].Journal of Xinjiang Agricultural University,2008,31(1):46-50.(in Chinese)
17 ZHENG C.Analysis of Cd pollution&spatial variability characteristics of typical agricultural soils in suburbs of Urumqi City,Xinjiang[J].Spectroscopy and Spectral Analysis,2012,32(2):537-540.
18 ZHENG Jiang,WANG Ling.Spatial variation characteristics of soil available lead in vegetable base soil in Urumqi City[J].Agricultural Sciences&Technology,2012,13(1):155-157.
19鲍士旦.土壤农化分析[M].北京:中国农业出版社,2000.
20尼加提·卡斯木,师庆东,王敬哲,等.基于高光谱特征和偏最小二乘法的春小麦叶绿素含量估算[J].农业工程学报,2017,33(22):208-216.NIJIATI Kasimu,SHI Qingdong,WANG Jingzhe,et al.Estimation of spring wheat chlorophyll content based on hyperspectral features and PLSR model[J].Transactions of the CSAE,2017,33(22):208-216.(in Chinese)
21李丹.基于优化光谱指数的小麦玉米冠层氮素含量估算[D].呼和浩特:内蒙古农业大学,2015.LI Dan.Optimaized spectral indices based on estimation of canopy nitrogen content in wheat and maize[D].Huhhot:Inner Monolia Agricultural University,2015.(in Chinese)
22张娟娟,田永超,姚霞,等.基于高光谱的土壤全氮含量估测[J].自然资源学报,2011,26(5):881-890.ZHANG Juanjuan,TIAN Yongchao,YAO Xia,et al.Estimating soil total nitrogen content based on hyperspectral analysis technology[J].Journal of Natural Resources,2011,26(5):881-890.(in Chinese)
23 JORDAN C F.Derivation of leaf-area index from quality of light on the forest floor[J].Ecology,1969,50(4):663-666.
24 ROUSE JR J W,HAAS R H,SCHELL J A,et al.Monitoring the vernal advancement and retrogradation(green wave effect)of natural vegetation[C]∥Prog Rep RSC1978-1,Remote Sensing Center,Texas A&M University,College Station,1973:93.
25 GITELSON A A,VINA A,ARKEBAUER T J,et al.Remote estimation of leaf area index and green leaf biomass in maize canopies[J].Geophysical Research Letters,2003,30(30):335-343.
26 WOLD S.PLS for multivariate linear modeling[J].Chemometric Methods in Molecular Design,1995,2:195-218.
27 MAIMAITIYIMING M,GHULAM A,BOZZOLO A,et al.Early detection of plant physiological responses to different levels of water stress using reflectance spectroscopy[J].Remote Sensing,2017,9(7):745.
28 BO S,ROSSEL R A V,MOUAZEN A M,et al.Chapter five-visible and near infrared spectroscopy in soil science[M]∥Advances in Agronomy.Elsevier Science&Technology,2010:163-215.
29 BAUMGARDNER M F,SILVA L F,BIEHL L L,et al.Reflectance properties of soils[J].Advances in Agronomy,1985,38:1-44.
30武彦清,张柏,宋开山,等.松嫩平原土壤有机质含量高光谱反演研究[J].中国科学院大学学报,2011,28(2):187-194.WU Yanqing,ZHANG Bai,SONG Kaishan,et al.Retrieval of soil organic matter content from hyper-spectra in Songnen Plain[J].Journal of the Graduate School of the Chinese Academy of Sciences,2011,28(2):187-194.(in Chinese)
31何挺,王静,林宗坚,等.土壤有机质光谱特征研究[J].地球空间信息科学学,2009,12(1):975-979.HE Ting,WANG Jing,LIN Zongjian,et al.Spectral features of soil organic matter[J].Geospatial Information Science,2009,12(1):975-979.(in Chinese)
32安海波.基于优化光谱指数的草地生物量估算[D].呼和浩特:内蒙古农业大学,2015.ZHANG Haibo.Estimating grassland biomass based on optimized spectral indices[D].Huhhot:Inner Monolia Agricultural University,2015.(in Chinese)
2王海峰,张智韬,ARNON K,等.基于灰度关联-岭回归的荒漠土壤有机质含量高光谱估算[J].农业工程学报,2018,34(14):124-131.WANG Haifeng,ZHANG Zhitao,ARNON K,et al.Estimation model of desert soil organic matter content using hyperspectral data[J].Transactions of the CSAE,2018,34(14):124-131.(in Chinese)
3田永超,张娟娟,姚霞,等.基于近红外光声光谱的土壤有机质含量定量建模方法[J].农业工程学报,2012,28(1):145-152.TIAN Yongchao,ZHANG Juanjuan,YAO Xia,et al.Quantitative modeling method of soil organic matter content based on nearinfrared photoacoustic spectroscopy[J].Transactions of the CSAE,2012,28(1):145-152.(in Chinese)
4宋海燕,秦刚,韩小平,等.基于可见光谱的不同质地土壤有机质快速测定[J/OL].农业机械学报,2012,43(7):69-72.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?file_no=20120712&flag=1.DOI:10.6041/j.issn.1000-1298.2012.07.012.SONG Haiyan,QIN Gang,HAN Xiaoping,et al.Rapid prediction of soil organic matter by using visible infrared spectral technology[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2012,43(7):69-72.(in Chinese)
5李美清,李晋阳.基于反射光谱特性的土壤有机质含量测定仪改进设计[J].农业机械学报,2008,39(10):148-151.LI Meiqing,LI Jinyang.Improved research on intellectual system for measuring soil organic matter content with spectrum method[J].Transactions of the Chinese Society for Agricultural Machinery,2008,39(10):148-151.(in Chinese)
6 KOOISTRA L,WANDERS J,EPEMA G F,et al.The potential of field spectroscopy for the assessment of sediment properties in river floodplains[J].Analytica Chimica Acta,2003,484(2):189-200.
7 KRISHNAN P,ALEXANDER J D,BUTLER B J,et al.Reflectance technique for predicting soil organic matter[J].Soil Science Society of America Journal,1980,44(6):1282-1285.
8王延仓,杨贵军,朱金山,等.基于小波变换与偏最小二乘耦合模型估测北方潮土有机质含量[J].光谱学与光谱分析,2014,34(7):1922-1926.WANG Yancang,YANG Guijun,ZHU Jinshan,et al.Estimation of organic matter content of north fluvo-aquic soil based on the coupling model of wavelet transform and partial least squares[J].Spectroscopy and Spectral Analysis,2014,34(7):1922-1926.(in Chinese)
9徐明星,周生路,丁卫,等.苏北沿海滩涂地区土壤有机质含量的高光谱估算[J].农业工程学报,2011,27(2):219-223.XU Mingxing,ZHOU Shenglu,DING Wei,et al.Hyperspectral reflectance models for predicting soil organic matter content in coastal tidal land area,northern Jiangsu[J].Transactions of the CSAE,2011,27(2):219-223.(in Chinese)
10 HUMMEL J W,SUDDUTH K A,HOLLINGER S E.Soil moisture and organic matter prediction of surface and subsurface soils using an NIR soil sensor[J].Computers and Electronics in Agriculture,2001,32(2):149-165.
11 CONFORTI M,BUTTAFUOCO G,LEONE A P,et al.Studying the relationship between water-induced soil erosion and soil organic matter using vis-NIR spectroscopy and geomorphological analysis:a case study in southern Italy[J].Catena,2013,110:44-58.
12 NOWKANDEH S M,HOMAEE M,NOROOZI A A.Mapping soil organic matter using hyperion images[J].International Journal of Agronomy&Plant Production,2013,4:1753-1759.
13栾福明,张小雷,熊黑钢,等.基于不同模型的土壤有机质含量高光谱反演比较分析[J].光谱学与光谱分析,2013,33(1):196-200.LUAN Fuming,ZHANG Xiaolei,XIONG Heigang,et al.Comparative analysis of soil organic matter content based on different hyperspectral inversion models[J].Spectroscopy and Spectral Analysis,2013,33(1):196-200.(in Chinese)
14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/OL].农业机械学报,2017,48(3):164-172.http:∥www.j-csam.org/jcsam/ch/reader/view_abstract.aspx?file_no=20170321&flag=1&journal_id=jcsam.DOI:10.6041/j.issn.1000-1298.2017.03.021.YE Qin,JIANG Xueqin,LI Xican,et al.Comparison on inversion model of soil organic matter content based on hyperspectral data[J/OL].Transactions of the Chinese Society for Agricultural Machinery,2017,48(3):164-172.(in Chinese)
15张小禹.乌鲁木齐市蔬菜基地土壤有效态镍的空间变异特征[J].新疆环境保护,2012,34(3):41-45.ZHANG Xiaoyu.Spatial variation characteristic of soil active nickel in Urumqi Vegetable Base[J].Environmental Protection of Xinjiang,2012,34(3):41-45.(in Chinese)
16王灵,朱建雯,钱翌,等.乌鲁木齐市菜地土壤和蔬菜铅含量及风险评价[J].新疆农业大学学报,2008,31(1):46-50.WANG Ling,ZHU Jianwen,QINA Yi,et al.Lead content in vegetable and soil of vegetable plot in Urumqi City and its risk evaluation[J].Journal of Xinjiang Agricultural University,2008,31(1):46-50.(in Chinese)
17 ZHENG C.Analysis of Cd pollution&spatial variability characteristics of typical agricultural soils in suburbs of Urumqi City,Xinjiang[J].Spectroscopy and Spectral Analysis,2012,32(2):537-540.
18 ZHENG Jiang,WANG Ling.Spatial variation characteristics of soil available lead in vegetable base soil in Urumqi City[J].Agricultural Sciences&Technology,2012,13(1):155-157.
19鲍士旦.土壤农化分析[M].北京:中国农业出版社,2000.
20尼加提·卡斯木,师庆东,王敬哲,等.基于高光谱特征和偏最小二乘法的春小麦叶绿素含量估算[J].农业工程学报,2017,33(22):208-216.NIJIATI Kasimu,SHI Qingdong,WANG Jingzhe,et al.Estimation of spring wheat chlorophyll content based on hyperspectral features and PLSR model[J].Transactions of the CSAE,2017,33(22):208-216.(in Chinese)
21李丹.基于优化光谱指数的小麦玉米冠层氮素含量估算[D].呼和浩特:内蒙古农业大学,2015.LI Dan.Optimaized spectral indices based on estimation of canopy nitrogen content in wheat and maize[D].Huhhot:Inner Monolia Agricultural University,2015.(in Chinese)
22张娟娟,田永超,姚霞,等.基于高光谱的土壤全氮含量估测[J].自然资源学报,2011,26(5):881-890.ZHANG Juanjuan,TIAN Yongchao,YAO Xia,et al.Estimating soil total nitrogen content based on hyperspectral analysis technology[J].Journal of Natural Resources,2011,26(5):881-890.(in Chinese)
23 JORDAN C F.Derivation of leaf-area index from quality of light on the forest floor[J].Ecology,1969,50(4):663-666.
24 ROUSE JR J W,HAAS R H,SCHELL J A,et al.Monitoring the vernal advancement and retrogradation(green wave effect)of natural vegetation[C]∥Prog Rep RSC1978-1,Remote Sensing Center,Texas A&M University,College Station,1973:93.
25 GITELSON A A,VINA A,ARKEBAUER T J,et al.Remote estimation of leaf area index and green leaf biomass in maize canopies[J].Geophysical Research Letters,2003,30(30):335-343.
26 WOLD S.PLS for multivariate linear modeling[J].Chemometric Methods in Molecular Design,1995,2:195-218.
27 MAIMAITIYIMING M,GHULAM A,BOZZOLO A,et al.Early detection of plant physiological responses to different levels of water stress using reflectance spectroscopy[J].Remote Sensing,2017,9(7):745.
28 BO S,ROSSEL R A V,MOUAZEN A M,et al.Chapter five-visible and near infrared spectroscopy in soil science[M]∥Advances in Agronomy.Elsevier Science&Technology,2010:163-215.
29 BAUMGARDNER M F,SILVA L F,BIEHL L L,et al.Reflectance properties of soils[J].Advances in Agronomy,1985,38:1-44.
30武彦清,张柏,宋开山,等.松嫩平原土壤有机质含量高光谱反演研究[J].中国科学院大学学报,2011,28(2):187-194.WU Yanqing,ZHANG Bai,SONG Kaishan,et al.Retrieval of soil organic matter content from hyper-spectra in Songnen Plain[J].Journal of the Graduate School of the Chinese Academy of Sciences,2011,28(2):187-194.(in Chinese)
31何挺,王静,林宗坚,等.土壤有机质光谱特征研究[J].地球空间信息科学学,2009,12(1):975-979.HE Ting,WANG Jing,LIN Zongjian,et al.Spectral features of soil organic matter[J].Geospatial Information Science,2009,12(1):975-979.(in Chinese)
32安海波.基于优化光谱指数的草地生物量估算[D].呼和浩特:内蒙古农业大学,2015.ZHANG Haibo.Estimating grassland biomass based on optimized spectral indices[D].Huhhot:Inner Monolia Agricultural University,2015.(in Chinese)