Predicting vegetation water content in wheat using normalized difference water indices derived from ground...

Area of Science:

• Environmental Science
• Agricultural Science
• Remote Sensing

Background:

• Vegetation water content (VWC) is crucial for agriculture and forest fire management.
• Remote sensing provides a non-destructive method for VWC assessment.
• Relating in situ VWC measurements to spectral reflectance is key for accurate estimation.

Purpose of the Study:

• To propose new normalized difference water indices (NDWI) for estimating VWC.
• To account for leaf internal structure and dry matter content in VWC estimation.
• To validate the proposed indices for fuel moisture content (FMC) and equivalent water thickness (EWT).

Main Methods:

• Developed three new NDWI using reflectance at 1,200, 1,450, and 1,940 nm, normalized by reflectance at 860 nm.
• Utilized radiative transfer models for index development.
• Assessed correlations between proposed indices and in situ FMC and EWT measurements.

Main Results:

• Strong correlations were found between FMC and the proposed NDWI (R² = 0.65–0.80).
• High correlations were observed for EWT at both leaf (R² = 0.75–0.81) and canopy scales (R² = 0.80–0.83).
• The indices showed good performance across various stages of wheat crop development.

Conclusions:

• The proposed NDWI are effective for estimating VWC, including FMC and EWT.
• These indices offer a reliable remote sensing approach for VWC assessment in agricultural and ecological studies.
• The findings support the use of these novel indices for improved vegetation monitoring.