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为探索适合黄河三角洲滨海地区土壤盐分含量的快速准确估测方法,以黄河三角洲垦利县为研究区,采用野外原位土壤高光谱数据与室内实测土样盐分数据相结合的分析方法,进行土壤盐分估测研究。通过对土壤盐分高光谱反射率、一阶微分反射率与盐分含量进行相关性分析,筛选出土壤盐分敏感波段;通过波段组合构建并筛选出土壤盐分敏感光谱参量;通过对敏感波段进行主成分回归建模、多元逐步线性回归建模和运用光谱参量建模,筛选出最佳的估测模型。结果显示:一阶微分可放大样品间的光谱特征差异,提高了相关性;波段组合可消除部分背景因素影响,与盐分的相关性明显提高;利用敏感光谱参量构建的估测模型优于直接用敏感波段构建的模型,土壤盐分最佳估测模型为y=0.623-2003920.934*X507*X772+0.259*(X512+X1093)-469.717*X772/X512,R2为0.591,验证R2为0.556,RPD为1.624,RMSE为0.116,拟合度较好,稳定性较高。该研究为滨海区土壤盐分含量的野外高光谱估测提供了新的方法,同时为土壤盐分含量的高光谱定量研究提供理论和技术参考。
In order to explore a rapid and accurate method for estimating soil salinity in the coastal areas of the Yellow River Delta, Kenli County in the Yellow River Delta was used as a study area. Soil samples were collected from the field using in situ soil hyperspectral data and indoor measured soil salt data. Salinity estimation research. Through the correlation analysis of hyperspectral reflectance, first-order differential reflectance and salt content of soil salinity, the salt-sensitive bands of soil were screened out; the salt-sensitive spectral parameters of soil were constructed and screened by band combination; Modeling, multivariate stepwise linear regression modeling and the use of spectral parametric modeling, screening out the best estimation model. The results show that the first-order differential can amplify the difference of spectral characteristics between samples and improve the correlation. The band combination can eliminate the influence of some background factors, and the correlation with the salt is obviously improved. The estimation model constructed by using the sensitive spectral parameters is better than the direct- Sensitive band construction model, the best soil salinity estimation model y = 0.623-2003920.934 * X507 * X772 + 0.259 * (X512 + X1093) -469.717 * X772 / X512, R2 was 0.591, R2 was 0.556, RPD was 1.624 , The RMSE is 0.116, the fitting degree is better and the stability is higher. The study provided a new method for the field hyperspectral estimation of soil salinity in the coastal area, and provided theoretical and technical reference for the hyperspectral study of soil salinity content.