本文選題：荒漠土壤 + 重金屬��； 參考：《農(nóng)業(yè)機械學報》2017年05期

【摘要】：為解決高光譜檢測土壤中痕量級重金屬含量存在的困難,提高土壤重金屬鉻含量檢測的準確度,利用新疆準東煤田周邊168個荒漠土壤樣本的重金屬鉻含量及其對應的高光譜數(shù)據(jù),運用分數(shù)階微分算法進行光譜數(shù)據(jù)預處理,最后利用全部波段進行偏最小二乘建模并進行可視化分析,旨在探討分數(shù)階微分預處理在高光譜數(shù)據(jù)估算荒漠土壤重金屬鉻含量的可能性。結(jié)果表明:原始光譜與吸光率變換的分數(shù)階微分模型均在1.8階微分處達到了最好的精度效果。吸光率變換1.8階微分模型為最優(yōu)模型,模型的校正均方根誤差為7.68 mg/kg,R_c~2=0.83,預測均方根誤差為8.39 mg/kg,R_p~2=0.78,相對分析誤差為2.14。最后利用鉻含量實測值與光譜預測值通過反距離加權(quán)法插值獲得研究區(qū)土壤重金屬鉻含量的空間分布,說明利用該方法對土壤重金屬鉻含量定量檢測并進行大尺度的空間分布反演在一定程度上是可行的,為荒漠土壤重金屬污染狀況的高光譜檢測提供了一定的科學依據(jù)和技術(shù)支持。
[Abstract]:In order to solve the difficulty of detecting trace heavy metals in soil by hyperspectral method, and to improve the accuracy of the determination of chromium in soil, Based on the heavy metal chromium content and its corresponding hyperspectral data of 168 desert soil samples around Zhendong coalfield in Xinjiang, the fractional differential algorithm was used to preprocess the spectral data. Finally, the partial least square modeling and visualization analysis were carried out in all bands to explore the possibility of fractional-order differential pretreatment in estimating the content of heavy metal chromium in desert soil by hyperspectral data. The results show that the fractional-order differential model of the original spectrum and absorptivity transformation achieves the best accuracy at the 1.8 order differential. The 1.8-order differential model of absorptivity transformation is the best model. The corrected RMS error of the model is 7.68 mg / kg ~ (-1) 路kg ~ (-1) ~ (-1). The RMS error of prediction is 8.39 mg / kg ~ (-1) 路kg ~ (-1) ~ 0.78, and the relative analysis error is 2.14 mg 路kg ~ (-1) 路kg ~ (-1) ~ (-1) ~ (-1). Finally, the spatial distribution of heavy metal chromium content in the soil of the study area was obtained by using the measured value of chromium content and the predicted value of spectrum through the inverse distance weighting method. It shows that it is feasible to use this method to quantitatively detect the content of heavy metal chromium in soil and to invert the spatial distribution of the heavy metal on a large scale to a certain extent. It provides scientific basis and technical support for hyperspectral detection of heavy metal pollution in desert soil.
【作者單位】： 新疆大學資源與環(huán)境科學學院;新疆大學綠洲生態(tài)教育部重點實驗室;
【基金】：“十二五”國家科技支撐計劃項目(2014BAC15B01) 國家自然科學基金重點項目(41130531)
【分類號】：X833

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本文編號：1817170