高光谱在土壤重金属信息提取中的应用与实现

Application and Realization of Hyperspectral Information Extraction of Heavy Metals in Soil

以建设一套基于光谱数据的土壤重金属信息提取系统为研究目标,总结了土壤重金属指标及其光谱学机理。在软件技术和数据库技术支持下,实现了土壤重金属光谱信息管理、处理、分析和应用。研究表明:土壤重金属元素在其特征波段上所显示的光谱特性,经过光谱预处理、变换和定量化提取,能够为建模提供理论依据。在计算光谱统计特征量基础上,采用光谱分析法,自动检索土壤重金属光谱特征位置。以东北黑土地机载高光谱CASI和SASI数据为例,计算了硒、锰和铁等元素的含量,最高硒元素含量达到了80.767 mg kg^(-1)。随着植被覆盖率的提升,硒、锰、锡和锌元素的含量随之升高,说明水稻吸收了部分金属元素,对特征波段反射率产生了影响。

The research goal was to build a set of soil spectral data information extraction system and to summarize the criteria for heavy metals and the spectroscopic mechanism. With the help of software and database technologies, the management, processing, analysis and application of soil heavy metal spectral information were realized. The results showed that the spectral characteristics of the heavy metal elements in soil on the characteristic bands could be used to provide theoretical basis for modeling. On the basis of calculating the statistical characteristics of the spectrum, the spectral characteristic position of soil heavy metals was retrieved automatically by spectral analysis. Taking the airborne hyperspectral CASI and SASI data of Black soil in the northeast of China as an example, the contents of selenium （Se）, manganese （Mg）, and iron （Fe） were calculated, and the highest Se content was 80.767 mg kg-1. With the increase of vegetation coverage, the contents of Se, Mg, tin and zinc increased, which indicated that the rice absorbed some of the metal elements and had an effect on the characteristic band reflectance.