| 周守东1
，桂 翔2
，王德高1.基于高光谱的土壤重金属含量预测模型[J].海南师范大学学报自科版,2025,38(1):91-100 |
| 基于高光谱的土壤重金属含量预测模型 |
| Hyperspectral-based Predictive Modeling of Soil Heavy Metal Concentration in A Typical Site in Wuhu City, Anhui Province, China |
| |
| DOI：10.12051/j.issn.1674-4942.2025.01.012 |
| 中文关键词: 高光谱 土壤重金属 预测模型 |
| 英文关键词: hyperspectral soil heavy metals predictive modeling |
| 基金项目:安徽省高校自然科学研究重大项目（2022AH040337）；安徽省高校优秀拔尖人才培育资助项目（gxbzZD2022145） |
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| 摘要点击次数: 186 |
| 全文下载次数: 155 |
| 中文摘要: |
| 利用高光谱遥感技术，通过分析土壤光谱特征与土壤中重金属含量之间的关系，建
立了预测土壤重金属含量的模型。该技术基于不同物质对电磁波的吸收和反射特性不同，可以
间接推测土壤中的化学成分。采用了高光谱测量的方法获取含重金属土壤样品谱图，经多种光
谱变换预处理后，建立了基于偏最小二乘回归算法（PLSR）的估测模型，并评价了模型的精度；
结合室内化学分析［电感耦合等离子体质谱（ICP-MS）］，测定了土壤样品中重金属含量。研究结果
表明，光谱活性物质特征谱段的提取以及土壤类型的考虑能够提高土壤重金属含量的反演精度。
此外，通过对比室内外结果，验证了高光谱遥感技术用于土壤重金属含量快速检测的可行性和准
确性。这一方法不仅提高了检测效率，降低了成本，还为大范围土壤污染的实时监测和管理提供
了新的技术手段，对指导农业生产、保护生态环境、预防和控制土壤污染具有重要意义。 |
| 英文摘要: |
| A model for estimating heavy metal content in soil by hyperspectral remote sensing technology was established
to analyze the relationship between soil spectral characteristics and the levels of heavy metals. Based on the distinct absorp⁃
tion and reflection properties of various materials by electromagnetic waves, this technology enabled the indirect prediction
of soil′s chemical composition. Hyperspectral measurements were employed to acquire spectral profiles of soil samples with
heavy metal elements. After multiple spectral transformation and preprocessing steps, a prediction model based on partial
least squares regression (PLSR) was constructed, and its accuracy was assessed. Additionally, laboratory-based chemical
analysis utilizing inductively coupled plasma mass spectrometry (ICP-MS) were integrated to calibrate the heavy metal con⁃
tent in soil samples. The findings indicated that the extraction of spectral active material signatures and consideration of
soil types significantly enhanced the inversion accuracy of heavy metal content prediction. Furthermore, a comparison of in⁃
door and outdoor results validated the feasibility and accuracy of hyperspectral remote sensing technology in rapidly detect⁃
ing soil heavy metal content. This innovative approach not only elevates the detection efficiency and reduced the costs but
also introduced the method with real-time monitoring and management of large-scale soil contamination. This study holds significant implications for guiding agricultural production, safeguarding ecological environments, and preventing and con⁃
trolling soil pollution. |
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