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[Soil moisture estimation model based on multiple vegetation index].

Hai-long Wu, Xin-xiao Yu, Zhen-ming Zhang

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
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    This summary is machine-generated.

    Accurate soil moisture estimation is crucial for agriculture and forestry. This study developed a non-contact method using multiple vegetation indexes derived from hyperspectral data, achieving high accuracy for water resource management.

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    Area of Science:

    • Environmental Science
    • Agricultural Science
    • Forestry Science

    Background:

    • Accurate soil moisture estimation is vital for water resource management in agriculture and forestry.
    • Existing methods for soil moisture estimation have limitations in convenience and precision.
    • Vegetation index-based approaches show promise for non-contact soil moisture assessment.

    Purpose of the Study:

    • To develop and validate a novel method for estimating soil moisture using multiple vegetation indexes.
    • To assess the accuracy and applicability of the developed model for micro-scale soil water content estimation.
    • To provide a convenient and precise alternative to traditional soil moisture measurement techniques.

    Main Methods:

    • Acquired hyperspectral data using a portable spectrometer.
    • Calculated eight vegetation indexes and selected the most correlated ones with surface vegetation temperature using Gray Relative Analysis (GRA).
    • Developed a soil moisture estimation model using Multiple Linear Regression (MLR) with selected vegetation indexes and evaluated its accuracy.

    Main Results:

    • The developed model demonstrated high accuracy, with R-squared (R2) reaching 0.636 and Root Mean Square Error (RMSE) of 2.149.
    • Statistical analysis confirmed the model's significance (P < 0.001), indicating a strong fit.
    • The method successfully estimated soil moisture using multiple vegetation indexes via a non-contact approach.

    Conclusions:

    • The developed multiple vegetation index model offers a convenient and accurate method for estimating soil moisture at a micro-scale.
    • This non-contact technique serves as a viable alternative to remote sensing inversion and direct soil moisture measurements.
    • The study provides a valuable theoretical and technological reference for effective water resource management in agricultural and forestry sectors.