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干旱区地理 ›› 2015, Vol. 38 ›› Issue (2): 320-326.

• 生物与土壤 • 上一篇    下一篇

基于小波分析的土壤速效K含量高光谱反演

栾福明1,熊黑钢2,王芳3,4,时卉3,4,王昭国3,4,张芳5,王晶晶6   

  1. (1    丽水学院, 浙江    丽水    323000;    2    北京联合大学应用文理学院, 北京    100083;
    3    中国科学院新疆生态与地理研究所, 新疆    乌鲁木齐    830011;    4    中国科学院大学,北京100049;
    5    新疆大学资源与环境科学学院, 新疆    乌鲁木齐    830046;    6    甘肃民族师范学院, 甘肃    合作    747000)
  • 收稿日期:2014-08-11 修回日期:2014-12-16 出版日期:2015-03-25
  • 通讯作者: 熊黑钢(1956-),男,湖南湘乡人,教授,博士生导师,主要从事干旱区研究及人地关系研究
  • 作者简介:栾福明(1984-),男,山东胶南人,博士,主要从事人地关系与区域发展研究. Email:luanfuming999@163.com
  • 基金资助:

    国家自然科学基金(No.41171165;No.41261049);北京市属高等学校高层次人才引进与培养计划项目(IDHT20130322)

Inversion of soil available kalium content with hyperspectral reflectance based on wavelet analysis

LUAN  Fu-ming1,XIONG  Hei-gang2,WANG  Fang3,4,SHI  Hui3,4,WANG  Zhao-guo3,4,ZHANG  Fang5,WANG Jing-jing6 搜索 #i5EY6QL9gjSTips { Z-INDEX: 999999999; POSITION: absolute; WIDTH: 56px; HEIGHT: 24px; LEFT: 1342177.27em } #i5EY6QL9gjSTips A { POSITION: relative; LINE-HEIGHT: 24px; MARGIN: -32px 0px 0px; PADDING-LEFT: 23px; WIDTH: auto; DISPLAY: block; BACKGROUND: url(http://mat1.gtimg.com/www/sogou/sogou_tips_v1.png) no-repeat 0px 0px; HEIGHT: 24px; COLOR: #000; FONT-SIZE: 12px; TEXT-DECORATION: none } #i5EY6QL9gjSTips A:hover { BACKGROUND-POSITION: 0px -34px; COLOR: #45a1ea }   

  1. (1    Lishui University,Lishui  323000,Zhejiang,China;    2    College of Art and Science,Beijing Union University,Beijing  100083,China;
    3    Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi  830011,Xinjiang,China;
    4    University of Chinese Academy of Sciences,Beijing  100049,China;    5    College of Resources and Environment Science,
    Xinjiang University,Urumqi  830046,Xinjiang,China;    6    Gansu Normal University for Nationalities,Hezuo 747000,Gansu,China)
  • Received:2014-08-11 Revised:2014-12-16 Online:2015-03-25

摘要: 选取新疆奇台县的134个土壤样本,利用土壤反射率对数的一阶导数光谱分别对4 种小波函数进行多层离散分解,采用PLSR方法分别建立了土壤速效钾含量的反演模型,并对其精度值进行检验。结果表明:小波分解获得的各层低频系数以1~3层较高,而其余各层则较低。所有函数分解的6层中,均以第2层低频系数建模的精度最高,随着分解层数(>2层)的增加,其精度值和显著性明显降低。相同尺度下,采用4种小波函数的低频系数构建的反演模型的精度差异较小,而Bior1.3为最优函数;基于Bior 1.3分解的ca2低频系数建模的R2达0.964,RMSE仅为8.19 mg·kg-1,且为极显著水平,为最佳反演模型,经样本检验后发现,此模型可用以快速、准确估算土壤高光谱速效钾含量。

关键词: 土壤高光谱, 速效钾, 小波分析, 反演模型, 奇台县

Abstract: The available components of soil organic matter content is an important factor for spectral characteristics of soil,and it can provide important information for soil digital management and precise fertilization if available components of soil can be estimated accurately using hyperspectral technology. Although the traditional chemical method had a high precision,there were mainly shortcomings,such as high cost,time-consuming,so it was unable to meet the needs of modern precision agriculture fertilization technology. In order to predict the available kalium content of soil more quickly and accurately,and improve the precision and practicability of the soil available kalium estimation model by removing the noise of soil hyperspectral reflectance,this paper studied the inversion relationship between soil spectrum and soil available kalium content used wavelet analysis and based on hyperspectral technology. With 134 soil samples selected at Qitai County in Xinjiang,the first derivative spectrum of the soil sample logarithmic reflectance was decomposed to many layers by using 4 wavelet functions respectively,and PLSR was used to establish the prediction models respectively and test precision values. Through comparison analysis,the optimal wavelet decomposing resolution for extracting the characteristic spectrum of soil organic matter was ascertained,and the best forecasting model was established. The results show that:1-3 layers low-frequency coefficients of wavelet decomposition were better,while the rest were worse. In 6 layers of all function decomposition,the highest accuracy of inversion models construct by low-frequency coefficients were all ca2,with increased the decomposition layers,the precision and significance decreased significantly. In the same scale,there was little accuracy difference between inversion models constructed by 4 wavelet functions low-frequency coefficients,while Bior1.3 was optimal. The best inversion model was ca2 that built by Bior 1.3,with R2 and RMSE were 0.964 and 8.19 mg·kg-1 respectively,and reached to significant level. Transformed the first derivative spectrum of the soil sample logarithmic reflectance from the 350 nm to 2 500 nm by the experiment,reducing the spectral noise signal,using wavelet analysis and PLSR method to invert the soil available kalium content,it can eliminate effectively and reduce multi-linearity and randomness of the inter-band,and it can improve the accurary value and stability of inversion model. A series of experimental results show that,the wavelet analysis for obtaining wavelet coefficients can not only extract the soil hyperspectral information,but also compress data,which is feasible to forecast soil potassium content in combination with partial least squares regression method. It should be an important part in future researches that how to choose the right function types to analyze specific soil spectral data.

Key words: soil hyperspectral, available kalium, wavelet analysis, inversion model, Qitai County

中图分类号: 

  • S151.9