Soil water content estimation based on hyperspectral reflectance with EPO correction salt interference

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Key Points

This research aims to accurately estimate soil water content while minimizing the interference of soil salinity on spectral data.
Field soil samples collected and prepared with varying salinity and moisture levels.
Hyperspectral reflectance data measured using a portable spectrometer and preprocessed with Savitzky-Golay smoothing and EPO transformation.
Several models including PLSR and RF were developed to estimate soil water content based on the processed data.
Soil moisture and salinity significantly affect the spectral reflectance from 350 to 1800 nm (P<0.01).
EPO correction effectively eliminated the impact of soil salinity on spectral reflectance, enhancing moisture estimation accuracy.
The RF model using EPO-corrected spectral indices achieved the highest performance with R2 values of 0.930 and 0.920 for calibration and validation sets, respectively.

Evaluates salt interference effects on soil water content estimation, highlighting EPO's importance.

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Chen et al. (2026) studied this question.

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