消除水分因素影响的野外原状土壤盐分高光谱建模估测

陈红艳1 赵庚星1 李玉环1 李华2 盖岳峰3

(1.土肥资源高效利用国家工程实验室/山东农业大学资源与环境学院, 泰安 271018)
(2.山东菏泽水利工程总公司, 菏泽 274000)
(3.山东颐通土地房地产评估测绘有限公司, 济南 250000)
【知识点链接】偏最小二乘回归

【摘要】土壤水分被确定为土壤属性 (有机碳、盐分等) 光谱预测准确性下降的一个主要原因, 该文通过两种方法的对比旨在探索去除土壤水分影响、提高盐分高光谱定量估测精度的方法和技术路线。首先以山东省东营市垦利区为研究区, 采用地物光谱仪测定了96个样本的野外原状土和室内风干土光谱, 并进行一阶导数变换;接着, 对比分析盐分光谱特征及水分的影响;然后分别采用外部参数正交化 (external parameter orthogonalization, EPO) 和非负矩阵分解 (non-negative matrix factorizing, NMF) 方法校正和融合野外原状土光谱, 去除土壤水分因素的影响, 形成野外原状土光谱的校正和融合光谱;最后基于野外原状土光谱、校正和融合光谱, 分别采用多元逐步线性回归 (multiple step linear regression, MSLR) 和偏最小二乘回归 (partial least squares regression, PLSR) 构建土壤盐分含量的估测模型, 并进行验证和比较, 分析预测精度变化。结果显示:土壤水分对野外原状土光谱及盐分光谱特征影响较大, 需要研究去除;EPO和NMF均可提高土壤盐分野外原位光谱估测精度, 比较而言, NMF效果更为显著;EPO结合PLSR或NMF结合MSLR可作为去除水分影响的土壤盐分校准模型的技术路线。

【关键词】 土壤盐分; 土壤水分; 光谱分析; 外部参数正交化; 非负矩阵分解;

【DOI】

【基金资助】 国家自然科学基金项目 (41401239, 41671346) 国家科技支撑计划 (2015BAD23B02) 山东农业大学“双一流”奖补资金资助 (SYL2017XTTD02) 山东省重点研发计划 (2017CXGC0306)

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This Article

ISSN:1002-6819

CN: 11-2047/S

Vol 34, No. 12, Pages 119-125

June 2018

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摘要

  • 0 引言
  • 1 材料与方法
  • 2 结果与分析
  • 3 讨论
  • 4 结论
  • 参考文献