[Research on remote sensing inversion biomass method based on the Suaeda salsa's measured spectrum]

Area of Science:

• Ecological remote sensing
• Wetland vegetation monitoring
• Plant biophysical parameter estimation

Background:

• Suaeda salsa is a key wetland plant in Northern China.
• Accurate monitoring of wetland vegetation is crucial for ecological management.
• Spectral characteristics can provide insights into plant health and biomass.

Purpose of the Study:

• To investigate the spectral characteristics of Suaeda salsa.
• To establish relationships between vegetation indices and Leaf Area Index (LAI).
• To assess the correlation between vegetation indices and biomass.

Main Methods:

• Field spectral measurements using a portable spectrometer.
• Leaf Area Index (LAI) measurements with a vegetation canopy analyzer.
• Biomass sampling and regression analysis to develop predictive models.

Main Results:

• Suaeda salsa exhibits distinct spectral features in the red band and red edge.
• Soil Adjusted Vegetation Index (SAVI) and Modified SAVI (MSAVI) showed the highest correlation with LAI (R²=0.711).
• SAVI and MSAVI also demonstrated strong correlations with biomass, particularly with quadratic regression models (R² up to 0.711).

Conclusions:

• Spectral analysis is effective for characterizing Suaeda salsa.
• SAVI and MSAVI are reliable vegetation indices for estimating LAI and biomass in Suaeda salsa.
• Remote sensing techniques can be valuable tools for wetland vegetation assessment.