张霞, 丁松滔, 岑奕, 孙伟超, 王晋年. 结合野外与实验室光谱的土壤Pb含量反演[J]. 武汉大学学报 ( 信息科学版), 2022, 47(9): 1479-1485. DOI: 10.13203/j.whugis20200386
引用本文: 张霞, 丁松滔, 岑奕, 孙伟超, 王晋年. 结合野外与实验室光谱的土壤Pb含量反演[J]. 武汉大学学报 ( 信息科学版), 2022, 47(9): 1479-1485. DOI: 10.13203/j.whugis20200386
ZHANG Xia, DING Songtao, CEN Yi, SUN Weichao, WANG Jinnian. Soil Heavy Metal Pb Content Estimation Method by Combining Field Spectra with Laboratory Spectra[J]. Geomatics and Information Science of Wuhan University, 2022, 47(9): 1479-1485. DOI: 10.13203/j.whugis20200386
Citation: ZHANG Xia, DING Songtao, CEN Yi, SUN Weichao, WANG Jinnian. Soil Heavy Metal Pb Content Estimation Method by Combining Field Spectra with Laboratory Spectra[J]. Geomatics and Information Science of Wuhan University, 2022, 47(9): 1479-1485. DOI: 10.13203/j.whugis20200386

结合野外与实验室光谱的土壤Pb含量反演

Soil Heavy Metal Pb Content Estimation Method by Combining Field Spectra with Laboratory Spectra

  • 摘要: 重金属污染日益加剧,重金属在土壤中的聚集不仅破坏了生态平衡,也对人类的健康生活造成了影响,因此快捷、准确地获取土壤中的重金属含量成为土壤污染监制与治理的重要环节。高光谱遥感技术的发展使得快速低成本反演土壤重金属含量成为可能。针对野外光谱受环境因素(土壤粒径、含水量等)的影响,且现有研究中普遍存在样本量不足的问题,提出结合野外光谱与实验室光谱构建土壤铅(Pb)反演机理模型的方法,首先,采用直接矫正(direct standardization,DS)算法对野外光谱进行环境因素校正;其次,通过引入实验室光谱联合建模的方式,提高样本的差异性;最后,提取铁氧化物特征谱段用于建模以增加反演的机理性。利用中国河北雄安一般农作区的70个土壤样本野外光谱数据研究表明,未经DS校正的野外光谱全谱段单独建模,反演精度R2仅为0.220 0,而所提方法的反演精度R2可达0.914 6, 模型具有出色的估算能力,表明在去除环境因素对野外光谱影响基础上,综合利用野外光谱与实验室光谱的铁氧化物特征谱段建模能够显著提高Pb含量的反演精度。

     

    Abstract:
      Objectives  The pollution of heavy metal has become increasingly serious in recent years. The accumulation of heavy metals in the soil will be a threat to ecological balance and human health. Therefore, we need to obtain heavy metal content in soil quickly and accurately.
      Methods  This paper proposes a method to combine field and laboratory spectra to construct a mechanism estimation model of soil lead (Pb). Firstly, direct standardization (DS) algorithm was employed to eliminate the influence of environmental factors on the field spectra. Secondly, in order to enhance the diversity of the samples, the laboratory spectra were introduced to joint modeling. Finally, the characteristic spectra of iron oxide were extracted for mod‍el‍ing to increase the model rationality.
      Results  This method was validated by the spectra of 70 soil samples from Xiong'an farming area in Hebei province. The accuracy R2 of model established by full-band field spectra without DS correction was only 0.220 0. However, the accuracy R2 of model established by the proposed method in this paper reached 0.914 6.
      Conclusions  It indicates that the model for estimating Pb content can be significantly improved by removing the influence of environmental factors on the field spectra, extracting the iron oxide characteristic spectra of the combining field spectra with laboratory spectra.

     

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