Hyperspectral inversion study of heavy metals content in soils of oasis farmland in arid region
Mamat SAWUT1,2,3, Abudugheni ABLIZ1,2,3, HU Xin1
1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China; 2. Xinjiang Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830017, China; 3. Key Laboratory of Smart City and Environment Modelling of Higher Education Institute, Xinjiang University, Urumqi 830017, China
Abstract:Analysis of the relationship between the content of six heavy metals (As, Hg, Pb, Cr, Zn, and Cu) in soil samples from the Ugan-Kuqa River Oasis in Xinjiang and hyperspectral data was conducted. Feature bands were selected based on the stepwise regression method, and soil heavy metal hyperspectral inversion models were constructed using Geographically Weighted Regression (GWR) and Ordinary Least Squares (OLS). 1) There were differences in the content of the six heavy metal elements in the study area, with the average content of heavy metals in the soil being Zn > Pb > Cr > Cu > As > Hg, all of which did not exceed the national soil background values. The average Pb content in the study area was higher than the local (Xinjiang) soil background value, indicating significant enrichment of Pb in the surface soil layer of the study area; 2) Different spectral transformations enhanced the spectral characteristics of soil heavy metals, but with some differences in intensity, with soil spectra after second-order differential transformation (SD) and first-order cube root differential transformation (CRFD) showing the most significant enhancement compared to the original spectra; 3) From the perspective of model validation, when inverting the content of the six soil heavy metal elements, the R2of GWR was higher than that of OLS, with the R2 of Zn approaching 0.8 and that of Cu approaching 0.6, indicating a certain predictive ability of the model, while the R2 of As, Hg, Pb, and Cr were still below 0.5, indicating that the predictive ability of the model was not ideal; 4) The spatial distribution of the six soil heavy metal contents predicted by the two models exhibited some spatial differences. Among them, the spatial distribution difference of As was the largest in these two prediction models, while the distribution of the other five heavy metal elements, Hg, Pb, Cr, Zn, and Cu, was relatively uniform. By estimating soil heavy metal contents through hyperspectral reflectance, efficient and rapid inversion of soil heavy metal contents in oasis farmland in arid areas had been achieved, providing reliable technical support for dynamic monitoring of soil heavy metal contents in oasis farmland in arid areas.
买买提·沙吾提, 阿不都艾尼·阿不里, 胡昕. 干旱区绿洲农田土壤重金属含量高光谱反演[J]. 中国环境科学, 2024, 44(4): 2208-2216.
Mamat SAWUT, Abudugheni ABLIZ, HU Xin. Hyperspectral inversion study of heavy metals content in soils of oasis farmland in arid region. CHINA ENVIRONMENTAL SCIENCECE, 2024, 44(4): 2208-2216.
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