高光谱土壤多元信息提取模型综述

高光谱土壤多元信息提取模型的精度与光谱学在这一领域未来能够发挥的作用直接相关。在列举土壤样品制备、理化成分测定和土壤光谱数据获取标准技术的基础上,总结了目前适用于土壤光谱处理的异常筛选、平滑去噪、重采样、变换和定量化方法。对偏最小二乘法、主成分分析和多元逐步回归法等8种建模方法进行了对比,分析了各类方法的建模针对性。按照有机质、水分、盐渍化、重金属和其它成分分类归纳了目前取得良好应用效果的多种光谱信息提取模型,并对比了每个模型的信息提取精度。光谱所指示的信息,不仅能够为土壤成分提供快速指示信息,而且在实测数据基础上所建立的信息提取模型,是软件研发、仪器研发和土质评价等工作的理论基础。

A review of hyperspectral multivariate information extraction models for soils

The accuracy of hyperspectral multivariate information extraction models for soil is directly related to the role of spectroscopy in the future.The paper has summarized the current methods which are suitable for soil spectral processing,including abnormal screening,smooth denoising,resampling,transform and quantitative methods on the basis of the lists of soil samples preparation, physical and chemical components determination and soil spectral data acquisition.In this paper,8 modeling methods such as partial least squares,principal component analysis and multiple stepwise regression are compared.The paper draws up a variety of spectral information extraction models which have achieved good results according to the organic matter,moisture content,salinity,heavy metals and other components.The information indicated by spectrum can provide a quick indication information for soil composition,and the information extraction model established based on the measured data is the theoretical basis for software development,instrument development and soil quality evaluation.