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中国沙漠 ›› 2014, Vol. 34 ›› Issue (5): 1320-1328.DOI: 10.7522/j.issn.1000-694X.2013.00231

• 生物与土壤 • 上一篇    下一篇

荒漠-绿洲交错带土壤N、P、K含量的高光谱反演模型

栾福明1,2, 熊黑钢3, 王芳1,2, 张芳4   

  1. 1. 中国科学院新疆生态与地理研究所, 新疆 乌鲁木齐 830011;
    2. 中国科学院大学, 北京 100049;
    3. 北京联合大学应用文理学院, 北京 100083;
    4. 新疆大学 资源与环境科学学院, 新疆 乌鲁木齐 830046
  • 收稿日期:2013-03-03 修回日期:2013-08-12 出版日期:2014-09-20 发布日期:2014-09-20
  • 作者简介:栾福明(1984-),男,山东胶南人,博士研究生,主要从事人地关系与区域发展研究。Email:luanfuming999@163.com
  • 基金资助:
    国家自然科学基金项目(41171165,41261049)资助

Hyperspectral Reflectance Inversion Models on Content of N, P, K of Soil in Oasis-Desert Ecotone

Luan Fuming1,2, Xiong Heigang3, Wang Fang1,2, Zhang Fang4   

  1. 1. Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. College of Art and Science, Beijing Union University, Beijing 100083, China;
    4. College of Resources and Environment Science, Xinjiang University, Urumqi 830046, China
  • Received:2013-03-03 Revised:2013-08-12 Online:2014-09-20 Published:2014-09-20

摘要: 利用新疆奇台县荒漠-绿洲交错带的75个土壤样本,选取土壤可见光-近红外光谱的反射率(R)、光谱反射率倒数之对数(lg(1/R))、光谱反射率一阶导数(FDR)和光谱波段深度(Depth)4个指标,分析了其与土壤N、P、K元素含量的关系,分别建立了反演模型并对其精度进行了检验。结果表明:可见光-近红外反射光谱快速估算荒漠-绿洲交错带土壤N、P、K元素含量的潜力大,其预测精度由高到低的排列顺序为:N>P>K。不同光谱指标反演模型的精度各异,指标DepthFDR的预测效果明显优于lg(1/R)和R,对N和P元素的拟合效果为:lg(1/R)<R<FDR<Depth,由Depth指标建立的反演模型最佳;而对K元素的反演精度则为:lg(1/R)<R<Depth<FDR,由FDR指标建立的反演模型精度最高。

关键词: 土壤光谱, 养分元素, 反演模型, 奇台县

Abstract: With 75 soil samples collected in Qitai County,Xinjiang, the spectral reflectance (R), logarithm of reciprocal spectral reflectance (lg(1/R)), first derivative spectral reflectance(FDR)and spectral band depth(Depth)were used to analyze the relationship between the visible-near infrared (VNIR) spectrum and the content of the nutrient elements N、P、K of the soil. Prediction models were established with tested precision levels. The results showed that: the VNIR had great potential to estimate rapidly three nutrient elements content of soil, and the order of prediction accuracy values for the nutrient elements was: N>P>K. The inversion model accuracy varied on different spectral indicators, and the predictive effect for Depth and FDR were obviously superior to lg (1/R) and R. The fitting effect of N and P elements was: lg(1/R)<R<FDR<Depth, and the inversion models established by the index of Depth were the best for N and P; while the inversion accuracy value for K element was: lg(1/R)<R<Depth<FDR, and the inversion model established by the index of FDR was optimal for K.

Key words: soil spectrum, nutrient elements, inversion model, Qitai County

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