数字农科院2.0

Ecological risk evaluation of heavy metals based on hyperspectral: a case study of rice paddy soil in Xiangtan County, China

文献类型： 外文期刊

作者： Tsogtbaatar, Undrakhtsetseg;Huo, Lili;Jiao, Le;Dalantai, Sainbayar;An, Yi;Batsaikhan, Bayartungalag;Jugnee, Unurnyam;Natsagdorj, Boldbaatar;Batsaikhan, Tsogtjargal;Munkhchuluun, Baasantsog

作者机构：

关键词： Ecological risk;Heavy metal;Hunan Province;Hyperspectral inversion;Rice paddy soil

期刊名称： ENVIRONMENTAL MONITORING AND ASSESSMENT

ISSN： 0167-6369

年卷期： 2025 年 197 卷 4 期

页码：

收录情况： SCIE（2025版） ; ; EI（2025版）

摘要： Heavy metal pollution in agricultural soils pose significant risks to food safety and human health, necessitating effective monitoring and assessment techniques. Recognizing characteristic spectral features is essential for accurately assessing the ecological risks associated with heavy metal pollution. To explore the potential of utilizing the hyperspectrum to evaluate ecologial risks of heavy metals pollution in paddy soil, the study investigated ecological risks and spectral characteristics (350 similar to 2500 nm) of heavy metals (Cd, Pb, Cr, Cu) in rice paddy soil in Xiangtan County, Hunan Province, China. Potential ecological risk index (RI) was employed to evaluate pollution level, and derivative transformations (first derivative R ' and second derivative R '') were applied to eliminate the hyperspectral noise. Results identified Cd as the primary pollutant in the paddy soil of Xiangtan County, followed by Pb, Cu, and Cr. Serious heavy metal pollution concentrated in riverine and cropland areas. After applying spectral transformations, the correlation between spectral reflectance and ecological risks significantly improved. The R '' transformation demonstrated the highest correlations for Cd (r = 0.95) at 2046 nm in high ecological risk category, while the R ' transformation exhibited the strongest negative correlation for Cd (r = - 0.94) at 2059 nm. This study highlights the potential of hyperspectral analysis as an effective tool for estimating ecological risks posed by heavy metal pollution in rice paddy soils. The findings provide valuable insights for improving monitoring practices and informing risk management strategies in agricultural environments.

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