耕层土壤有机质高光谱间接估测模型
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摘要
针对光学遥感技术只能获取表层土壤光谱信息而无法直接估测耕层土壤有机质含量的问题,探索建立基于表层土壤高光谱信息的耕层土壤有机质间接估测模型。以山东省济南市章丘区采集的76个表层、耕层土壤样本数据为基础,首先分析原始光谱反射率的光谱特征;然后利用反射率的一阶微分、平方根的一阶微分和对数倒数的一阶微分等方法对原始光谱反射率进行变换,并根据极大相关性原则选取估测因子;最后根据表层土壤有机质含量与耕层有机质含量间的内在关系,建立耕层土壤有机质含量的间接估测模型。结果表明,以557、1 621、2 107和2 316 nm波段对数倒数的一阶微分变换值和864 nm波段反射率平方根倒数一阶微分的变换值为估测因子,使用二次函数关系模型对耕层土壤有机质含量间接估测的精度最高,其决定系数R~2为0.784,平均相对误差为10.7%。研究表明,利用表层土壤高光谱信息间接估测耕层有机质含量可行有效。
An indirect estimation model of the soil organic matter content in the plough layer of the topsoil is established based on the hyperspectral information in view of the problem. The optical remote sensing techniques can only obtain the spectral information of topsoil, but can not estimate the content of organic in plough layer. Based on the data of 76 surface and ploughed soil samples collected in Zhangqiu district of Shandong Province, the spectral characteristics of the original spectral reflectance is firstly analyzed. Then, the original spectral reflectivity is transformed by the first-order differential of reflectivity, the first-order differential of square root and the first-order differential of logarithm of reciprocal. And the estimation factor is selected according to the principle of maximal correlation. Finally, based on the intrinsic relationship between the soil organic matter content and the organic matter content of the plough layer, an indirect estimation model of soil organic matter content in plough layer is established. The results show that the estimation factor is based on the first-order differential transformation of logarithmic reciprocal at 557 nm, 1 621 nm, 2 107 nm and 2 316 nm bands and the first-order differential transformation of the reciprocal square root of reflectivity at 864 nm bands,and quadratic function relationship model is the most accurate method for indirect estimation the content of organic in plough layer. The determination coefficient R~2 is 0.784, and the average relative error is 10.7%. The result shows that it is feasible and effective to estimate the organic matter content in topsoil indirectly by using hyperspectral information of topsoil.
An indirect estimation model of the soil organic matter content in the plough layer of the topsoil is established based on the hyperspectral information in view of the problem. The optical remote sensing techniques can only obtain the spectral information of topsoil, but can not estimate the content of organic in plough layer. Based on the data of 76 surface and ploughed soil samples collected in Zhangqiu district of Shandong Province, the spectral characteristics of the original spectral reflectance is firstly analyzed. Then, the original spectral reflectivity is transformed by the first-order differential of reflectivity, the first-order differential of square root and the first-order differential of logarithm of reciprocal. And the estimation factor is selected according to the principle of maximal correlation. Finally, based on the intrinsic relationship between the soil organic matter content and the organic matter content of the plough layer, an indirect estimation model of soil organic matter content in plough layer is established. The results show that the estimation factor is based on the first-order differential transformation of logarithmic reciprocal at 557 nm, 1 621 nm, 2 107 nm and 2 316 nm bands and the first-order differential transformation of the reciprocal square root of reflectivity at 864 nm bands,and quadratic function relationship model is the most accurate method for indirect estimation the content of organic in plough layer. The determination coefficient R~2 is 0.784, and the average relative error is 10.7%. The result shows that it is feasible and effective to estimate the organic matter content in topsoil indirectly by using hyperspectral information of topsoil.
引文
[1] 于雷,洪永胜,耿雷,等.基于偏最小二乘回归的土壤有机质含量高光谱估算[J].农业工程学报,2015,31(14):103-109.YU L,HONG Y S,GENG L,et al.Hyperspectral estimation of soil organic matter content based on partial least squares regression[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(14):103-109.
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[10] 侯艳军,塔西甫拉提·特依拜,买买提·沙吾提,等.荒漠土壤有机质含量高光谱估算模型[J].农业工程学报,2014,30(16):113-120.HOU Y J,TASHPOLAT T,MAMAT S,et al.Estimation model of desert soil organic matter content using hyperspectral data [J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(16):113-120.
[11] 陈红艳,赵庚星,张晓辉,等.去除水分影响提高土壤有机质含量高光谱估测精度[J].农业工程学报,2014,30(8):91-100.CHEN H Y,ZHAO G X,ZHANG X H,et al.Improving estimation precision of soil organic matter content by removing effect of soil moisture from hyperspectra[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(8):91-100.
[12] YANG H,KUANG B,MOUAZEN A.Quantitative analysis of soil nitrogen and carbon at a farm scale using visible and near infrared spectroscopy coupled with wavelength reduction[J].European Journal of Soil Science,2012,63(3):410-420.
[13] LIU F,ROSSITER D G,SONG X D,et al.A similarity-based method for three-dimensional prediction of soil organic matter concentration[J].Geoderma,2015,263(1):254-263.
[14] LIU S L,AN N N,YANG J J,et al.Prediction of soil organic matter variability associated with different land use types in mountainous landscape in southwestern Yunnan province,China[J].Catena,2015,133(10):137-144.
[15] 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预测[J].农业工程学报,2011,27(2):219-223.XU M X,ZHOU S L,DING W,et al.Hyperspectral reflectance models for predicting soil organic matter content in coastal tidal land area,northern Jiangsu[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(2):219-223.
[16] SHEPHERD K D,WALSH M G.Development of reflectance spectral libraries for characterization of soil properties[J].Soil Science Society of America Journal,2002,66(3):988-992.
[17] 刘娇,李毅,刘世宾.光谱测定黑河上游土壤有机质的预测模型[J].光谱学与光谱分析,2013,33(12):3354-3358.LIU J,LI Y,LIU S B.Prediction models of soil organic matter based on spectral curve in the upstream of heihe basin[J].Spectroscopy and Spectral Analysis,2013,33(12):3354-3358.
[18] 韩兆迎,朱西存,刘庆,等.黄河三角洲土壤有机质含量的高光谱反演[J].植物营养与肥料学报,2014,20(6):1545-1552.HAN Z Y,ZHU X C,LIU Q,et al.Hyperspectral inversion models for soil organic matter content in the Yellow River Delta[J].Journal of Plant Nutrition and Fertilizer,2014,20(6):1545-1552.
[19] 叶勤,姜雪芹,李西灿,等.基于高光谱数据的土壤有机质含量估测模型比较[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.
[20] 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估测比较分析[J].光谱学与光谱分析,2013,33(1):196-200.LUAN F M,ZHANG X L,XIONG H G,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.
[21] NAVEEN J P A,ABDELRAHMAN A H,LEWIS D B,et al.Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands[J].International Journal of Applied Earth Observation and Geoinformation,2014,33(11):47-56.
[22] 南锋,朱洪芬,毕如田.黄土高原煤矿区复垦农田土壤有机质含量的高光谱估测[J].中国农业科学,2016,49(11):2126-2135.NAN F,ZHU H F,BI R T.Hyperspectral prediction of soil organic matter content in the reclamation cropland of coal mining areas in the loess plateau[J].Scientia Agricultura Sinica,2016,49(11):2126-2135.
[23] 李媛媛,李微,刘远,等.基于高光谱遥感土壤有机质含量预测研究[J].土壤通报,2014,45(6):1313-1318.LI Y Y,LI W,LIU Y,et al.Study on the prediction of soil organic matter content based on hyperspectral remote sensing[J].Chinese Journal of Soil Science,2014,45(6):1313-1318.
[24] 李希灿,王静,王芳,等.基于模糊识别的土壤性质指标光谱估测[J].辽宁工程技术大学学报(自然科学版),2010,29(2):324-327.LI X C,WANG J,WANG F,et al.Spectral retrieved deduction of suil properties index based on fuzzy recognition theory[J].Journal of Liaoning Technical University (Natural Science),2010,29(2):324-327.
[25] 李西灿,赵庚星,陈红艳,等.土壤有机质含量区间值高光谱估测[J].测绘科学技术学报,2014,31(6):593-597;602.LI X C,ZHAO G X,CHEN H Y,et al.The interval estimation of soil organic matter content based on hyper-spctural data[J].Journal of Geomatics Science and Technology,2014,31(6):593-597;602.
[26] LI X C,YU T,WANG X.The soil organic matter content grey relationship inversion pattern based on hyper-spectral technique[J].Grey System:Theory and Application,2011,1(3):261-267.
[2] STENBERG B.Effects of soil sample pretreatments and standardised rewetting as interacted with sand classes on vis-NIR prediction of clay and soil organic carbon[J].Geoderma,2010,158(1):15-22.
[3] CECILE G,PHILIPPE L,GUILLAUME C.Regional predictions of eight common soil properties and their spatial structures from hyperspectral vis-NIR data[J].Geoderma,2012,189(6):176-185.
[4] 卢艳丽,白由路,杨俐苹,等.基于高光谱的土壤有机质含量预测模型的建立与评价[J].中国农业科学,2007,40(9):1989-1995.LU Y L,BAI Y L,YANG L P,et al.Prediction and validation of soil organic matter content based on hyperspectrum[J].Scientia Agricultura Sinica,2007,40(9):1989-1995.
[5] KARNIELI A,VERCHOVSKY I,HALL J K,et al.Geographic information system for semi-detailed mapping of soils in a semi-arid region[J].Geocarto Internatinal,1998,13(3):29-42.
[6] 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.
[7] CLOUTIS E A.Review article hyperspectral geological remote sensing:Evaluation of analytical techniques [J].Remote Sensing,1993,17(12):2215-2242.
[8] 彭杰,周清,张杨珠,等.有机质对土壤光谱特性的影响研究[J].土壤学报,2013,50(3):517-524.PENG J,ZHOU Q,ZHANG Y Z,et al.Effect of soil organic matter on spectral characteristics of soil[J].Acta Pedologica Sinica,2013,50(3):517-524.
[9] NOCITA M,STEVENS A,NOON C,et al.Prediction of soil organic carbon for different levels of soil moisture using vis-NIR spectroscopy[J].Geoderma,2013.DOI:10.1016/j.geoderma.2012.07.020.
[10] 侯艳军,塔西甫拉提·特依拜,买买提·沙吾提,等.荒漠土壤有机质含量高光谱估算模型[J].农业工程学报,2014,30(16):113-120.HOU Y J,TASHPOLAT T,MAMAT S,et al.Estimation model of desert soil organic matter content using hyperspectral data [J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(16):113-120.
[11] 陈红艳,赵庚星,张晓辉,等.去除水分影响提高土壤有机质含量高光谱估测精度[J].农业工程学报,2014,30(8):91-100.CHEN H Y,ZHAO G X,ZHANG X H,et al.Improving estimation precision of soil organic matter content by removing effect of soil moisture from hyperspectra[J].Transactions of the Chinese Society of Agricultural Engineering,2014,30(8):91-100.
[12] YANG H,KUANG B,MOUAZEN A.Quantitative analysis of soil nitrogen and carbon at a farm scale using visible and near infrared spectroscopy coupled with wavelength reduction[J].European Journal of Soil Science,2012,63(3):410-420.
[13] LIU F,ROSSITER D G,SONG X D,et al.A similarity-based method for three-dimensional prediction of soil organic matter concentration[J].Geoderma,2015,263(1):254-263.
[14] LIU S L,AN N N,YANG J J,et al.Prediction of soil organic matter variability associated with different land use types in mountainous landscape in southwestern Yunnan province,China[J].Catena,2015,133(10):137-144.
[15] 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预测[J].农业工程学报,2011,27(2):219-223.XU M X,ZHOU S L,DING W,et al.Hyperspectral reflectance models for predicting soil organic matter content in coastal tidal land area,northern Jiangsu[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(2):219-223.
[16] SHEPHERD K D,WALSH M G.Development of reflectance spectral libraries for characterization of soil properties[J].Soil Science Society of America Journal,2002,66(3):988-992.
[17] 刘娇,李毅,刘世宾.光谱测定黑河上游土壤有机质的预测模型[J].光谱学与光谱分析,2013,33(12):3354-3358.LIU J,LI Y,LIU S B.Prediction models of soil organic matter based on spectral curve in the upstream of heihe basin[J].Spectroscopy and Spectral Analysis,2013,33(12):3354-3358.
[18] 韩兆迎,朱西存,刘庆,等.黄河三角洲土壤有机质含量的高光谱反演[J].植物营养与肥料学报,2014,20(6):1545-1552.HAN Z Y,ZHU X C,LIU Q,et al.Hyperspectral inversion models for soil organic matter content in the Yellow River Delta[J].Journal of Plant Nutrition and Fertilizer,2014,20(6):1545-1552.
[19] 叶勤,姜雪芹,李西灿,等.基于高光谱数据的土壤有机质含量估测模型比较[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.
[20] 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估测比较分析[J].光谱学与光谱分析,2013,33(1):196-200.LUAN F M,ZHANG X L,XIONG H G,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.
[21] NAVEEN J P A,ABDELRAHMAN A H,LEWIS D B,et al.Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands[J].International Journal of Applied Earth Observation and Geoinformation,2014,33(11):47-56.
[22] 南锋,朱洪芬,毕如田.黄土高原煤矿区复垦农田土壤有机质含量的高光谱估测[J].中国农业科学,2016,49(11):2126-2135.NAN F,ZHU H F,BI R T.Hyperspectral prediction of soil organic matter content in the reclamation cropland of coal mining areas in the loess plateau[J].Scientia Agricultura Sinica,2016,49(11):2126-2135.
[23] 李媛媛,李微,刘远,等.基于高光谱遥感土壤有机质含量预测研究[J].土壤通报,2014,45(6):1313-1318.LI Y Y,LI W,LIU Y,et al.Study on the prediction of soil organic matter content based on hyperspectral remote sensing[J].Chinese Journal of Soil Science,2014,45(6):1313-1318.
[24] 李希灿,王静,王芳,等.基于模糊识别的土壤性质指标光谱估测[J].辽宁工程技术大学学报(自然科学版),2010,29(2):324-327.LI X C,WANG J,WANG F,et al.Spectral retrieved deduction of suil properties index based on fuzzy recognition theory[J].Journal of Liaoning Technical University (Natural Science),2010,29(2):324-327.
[25] 李西灿,赵庚星,陈红艳,等.土壤有机质含量区间值高光谱估测[J].测绘科学技术学报,2014,31(6):593-597;602.LI X C,ZHAO G X,CHEN H Y,et al.The interval estimation of soil organic matter content based on hyper-spctural data[J].Journal of Geomatics Science and Technology,2014,31(6):593-597;602.
[26] LI X C,YU T,WANG X.The soil organic matter content grey relationship inversion pattern based on hyper-spectral technique[J].Grey System:Theory and Application,2011,1(3):261-267.
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