Research on Soil Nutrient Content Estimated Model by Hyperspectral Remote Sensing Data

doi:10.6048/j.issn.1001-4330.2018.03.011

Xinjiang Agricultural Sciences ›› 2018, Vol. 55 ›› Issue (3): 490-495.DOI: 10.6048/j.issn.1001-4330.2018.03.011

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Research on Soil Nutrient Content Estimated Model by Hyperspectral Remote Sensing Data

QI Ya-qin^1,2, ZHANG Xian-feng¹, ZHANG Li-fu³, LV Xin², ZHANG Ze² , CHEN Jian², LI Xin-wei², WANG Fei², PENG Kui²

1.School of Earth and Space Sciences, Peking University/ Institute of Remote Sensing, Beijing 100871, China;
2.Key Laboratory of Oasis Eco-agriculture of Xinjiang Production and Construction Corps, College of Agronomy, Shihezi University, Shihezi Xinjiang 832003, China;
3 Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China

Online:2018-03-20 Published:2018-06-28

基于高光谱数据的农田土壤养分含量估测模型研究

祁亚琴^1,2,张显峰¹,张立福³,吕新²,张泽²,陈剑²,
李新伟²,王飞²,彭奎²

1.北京大学地球与空间科学学院/遥感研究所生态遥感实验室,北京 100871;
2.石河子大学/新疆兵团绿洲生态农业重点实验室,新疆石河子 832003;
3.中国科学院遥感与数字地球研究所高光谱研究室,北京 100094

通讯作者: 吕新(1966-),男,河北人,教授,博士,博士生导师,研究方向为数字农业,(E-mail)lxshz@126.com
作者简介:祁亚琴(1979-),女,副教授,博士,博士后,研究方向为精准农业、农业遥感与信息技术,(E-mail)qiaqia0412@21cn.com
基金资助:
国家自然科学基金项目“基于高光谱遥感数据的土壤主要养分含量信息的获取研究”(61465011);国家留学基金(201405215035);石河子大学青年教师与对口支援高校名师“结对子”培养(SDJDZ201509);石河子市科技攻关“利用3S技术快速监测农田土壤信息研究与示范”(2013GY01)项目

Abstract

Abstract: 【Objective】 To obtain the real-time, non-contact and non-destructive information of main nutrients (TN, TP and TK) of farmland soil quickly.【Method】Soil nutrient content model was established by spectral feature analysis techniques and sensitive wavebands.【Result】NDI-based estimates of the soil nutrient content prediction model with exponential function model(Y^TN =0.000,5 e^{4.700,3 xNDI})was the best to estimate TN; a cubic function model(Y_TP =802.27 x_NDI³-412.32 x_NDI²+72.357 x_NDI-3.318,9)was the best to estimate TP; a cubic function model(Y_TK =80,189 x_NDI³-11,471 x_NDI²+490.57 x_NDI+13.879)was the best to estimate TK content.【Conclusion】The results showed that the hyperspectral remote sensing quantitative model based on normalized spectral index (NDI) can be used to invert the content of TN, TP and TK in soil and achieve a good prediction effect through the precision evaluation of the model and repeated verification in fields.

Key words: hyperspectral remote sensing; soils; nutrient content; prediction model

摘要： 【目的】快速、实时、准确、无损地获取农田土壤主要养分(全氮TN、全磷TP、全钾TK)含量的信息。【方法】运用各种土壤反射率的光谱特征分析技术,提取其最具代表性的敏感波段位置,建立土壤养分含量反演模型。【结果】建立估算模型中,预测TN含量以指数函数模型(Y_TN=0.000 5e^{4.700 3}^xNDI)为最佳;预测TP含量以一元三次函数模型(Y_TP=802.27 x_NDI³-412.32 x_NDI²+72.357 x_NDI-3.318 9)为最佳;预测TK含量以一元三次函数模型(Y_TK=80 189 x_NDI³-11 471 x_NDI²+490.57 x_NDI+13.879)为最佳模型。【结论】通过模型精度评价和田间反复验证,基于归一化光谱指数NDI建立的高光谱遥感定量模型,能较好的反演土壤TN、TP、TK含量,达到良好的预测效果。

关键词: 高光谱遥感, 土壤, 养分含量, 预测模型

CLC Number:

S153

QI Ya-qin, ZHANG Xian-feng, ZHANG Li-fu, LV Xin, ZHANG Ze , CHEN Jian, LI Xin-wei, WANG Fei, PENG Kui. Research on Soil Nutrient Content Estimated Model by Hyperspectral Remote Sensing Data[J]. Xinjiang Agricultural Sciences, 2018, 55(3): 490-495.

祁亚琴,张显峰,张立福,吕新,张泽,陈剑,
李新伟,王飞,彭奎. 基于高光谱数据的农田土壤养分含量估测模型研究[J]. 新疆农业科学, 2018, 55(3): 490-495.

References

[1] 王人潮,苏海萍,王深法.浙江省主要土壤光谱反射特性及其模糊分类在土壤分类中的应用研究[J].浙江农业大学学报,1986,12(4):464-471.
WANG Ren-chao, SU Hai-ping, WANG Shen-fa. (1986). Spectral Reflectance Characteristics and Its Fuzzy Classification Applied to Soil Classification in Zhejiang Province [J]. Journal of Zhejiang Agricultural University, 12(4):464-471. (in Chinese)
[2] 张仁华.实验遥感模型及地面基础[M].北京:科学出版社,1992.
ZHANG Ren-hua. (1992). Experimental Remote Sensing Model and Ground Foundation [M]. Beijing: Science Press. (in Chinese)
[3] 刘良云.高光谱遥感在精准农业中的应用研究[R].中国科学院遥感应用研究所博士后出站报告,2002:38-45.
LIU Liang-yun. (2002). Application of Hyperspectral Remote Sensing in Precision Agriculture [R]. Postdoctoral Report of Institute of Remote Sensing Applications, Chinese Academy of Sciences: 38-45. (in Chinese)
[4] 郑兰芬,童庆禧,王晋年,等.高光谱分辨率遥感进展,遥感科学进展[M].北京:科学出版社,1995:1-175.
ZHENG Lan-fen, TONG Qin-xi, WANG Jin-nian, et al. (1995). Progress in Remote Sensing of Hyperspectral Resolution, Advances in Remote Sensing Science [M]. Beijing: Science Press: 1-175. (in Chinese)
[5] Bendor, E., & Banin, A. (1995). Near-infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Science Society of America Journal, 59(2): 364-372.
[6] Chodak, M., Ludwig, B., Khanna, P., & Beese, F. (2015). Use of near infrared spectroscopy to determine biological and chemical characteristics of organic layers under spruce and beech stands. Journal of Plant Nutrition and Soil Science,165(1): 27-33.
[7] 彭玉魁,张建新,何绪生,等.土壤水分、有机质和总氮含量的近红外光谱分析研究[J].土壤学报,1998,(35):554-559.
PENG Yu-kui, ZHANG Jiang-xin, HE Xu-sheng, et al. (1998). Analysis of Soil Moisture, Organic Matter and Total Nitrogen by Near Infrared Spectroscopy [J]. Acta Pedologica Sinica, (35):554-559. (in Chinese)
[8] 徐永明,蔺启忠,黄秀华,等.利用可见光、近红外反射光谱估算土壤总氮含量的实验研究[J].地理与地理信息科学,2005,21(1):19-22.
XU Yong-ming, Lin Qi-zhong, HUANG Xiu-hua, et al. (2005). Experimental Study on Estimating Total Nitrogen in Soil Using Visible Light and Near Infrared Reflectance Spectroscopy [J]. Geography and Geo-information Science, 21(1):19-22. (in Chinese)
[9] 宋海燕.基于光谱技术的土壤、作物信息获取及其相互关系的研究[D].杭州:浙江大学博士学位论文.2005:1-130.
SONG Hai-yan. (2005). Simulation of soil and crop information and their relationship based on spectral techniques[D]. PhD Dissertation. Zhejiang University, Hanzhou: 1-130. (in Chinese)
[10] 李伟,张书慧,张倩,等.近红外光谱法快速测定土壤碱解氮、速效磷和速效钾含量[J].农业工程学报,2007,23(1):55-59.
LI Wei, ZHANG Shu-hui, ZHANG Qian, et al. (2007). Rapid Determination of Soil Available Nitrogen, Available Phosphorusand Available Potassium by Near Infrared Spectroscopy [J]. Journal of Agricultural Engineering, 23(1):55-59. (in Chinese)
[11] 于飞健,闵顺耕,巨晓棠,等.近红外光谱法分析土壤中的有机质和氮素[J].分析试验室,2002,21(3):49-51.
YU Fei-jian, MIN Shun-geng, JU Xiao-tang, et al. (2002). Analysis of Soil Organic Matter and Nitrogen by Near Infrared Spectroscopy [J]. Analysis Laboratory, 21(3): 49-51. (in Chinese)
[12] 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 Ru-kun. (2000). Soil agricultural chemical analysis [M]. Beijing : China Agricultural Science and Technology Publishing House. (in Chinese)
[13] 鲍士旦,土壤农化分析[M].北京:中国农业出版社, 2000.
BAO Shi-dan.(2000). Analysis of Soil Agriculture [M]. Beijing: China Agricultural Press. (in Chinese)
[14] 刘磊,沈润平,丁国香.基于高光谱的土壤有机质含量估算研究 [J]. 光谱学与光谱分析,2011,(3):762-766.
LIU Lei, SHEN Run-ping, DING Guo-xiang. (2011). Estimation of Soil Organic Matter Based on Hyperspectral Spectra and Spectral Analysis [J]. Spectroscopy and Spectral Analysis, (3):762-766. (in Chinese)
[15]陈彦,吕新.基于FCM的绿洲农田养分管理分区研究[J].中国农业科学,2008,(7):2016-2024.
Yan Chen,Xin LV.(2008). Partition based on FCM oasis farmland nutrient management study [J]. Chinese Agriculture Science ,(7):2016-2024.

Research on Soil Nutrient Content Estimated Model by Hyperspectral Remote Sensing Data

基于高光谱数据的农田土壤养分含量估测模型研究

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