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通过典型研究区不同盐渍化土壤光谱反射率数据的变换和分析,选择与土壤含盐量响应敏感波段,建立实测高光谱土壤含盐量反演模型,以校正HSI影像建立的土壤含盐量反演模型。结果表明:实测高光谱土壤含盐量反演模型与HSI影像土壤含盐量反演模型均有较好的精度,模型判定系数(R2)均高于0.57,且模型稳定性较好。校正后的HSI影像土壤含盐量反演模型,模型判定系数有了较大提高,R2从0.571提升至0.681,且通过了0.01的显著性水平,均方根误差(RMSE)值为0.277。模型能够较好地提高区域尺度条件下土壤盐渍化监测精度,运用此方法开展盐渍化土壤定量遥感监测是可行的。
Through the transformation and analysis of the spectral reflectance data of different salinized soils in the typical study area, the response-sensitive bands of soil salinity were selected and the inversed soil salt content of the measured hyperspectral soil was established to correct the soil salinity Inversion model. The results show that both the measured hyperspectral soil salinity inversion model and the HSI image soil salinity inversion model have good accuracy. The model determination coefficient (R2) is higher than 0.57, and the model stability is good. The calibrated HSI image soil salinity inversion model shows that the coefficient of model determination has been greatly improved. The R2 increases from 0.571 to 0.681 and passes the significance level of 0.01 with a root mean square error (RMSE) of 0.277. The model can effectively improve the monitoring accuracy of soil salinization under the regional scale. It is feasible to use this method to carry out the quantitative remote sensing monitoring of salinized soil.