研究目的
Investigating the application of hyperspectral remote sensing in the quantification of grassland areas’ physiological and biochemical parameters, specifically focusing on the estimation of alpine grassland biomass.
研究成果
The study confirmed the effectiveness and feasibility of using hyperspectral remote sensing for large-scale and long-time sequence remote sensing biomass estimation in alpine grasslands. The model demonstrated high inversion accuracy and the ability to reflect biomass volume accurately.
研究不足
The study did not distinguish biomass differences of various types of grass seeds and ignored underground biomass indices, which may influence spectral characteristics.
1：Experimental Design and Method Selection:
The study utilized ground spectral observations and multisensor satellite remote sensing data, employing correlation analysis, scaling up, and regression analysis to establish a multiscale remote sensing inversion model for alpine grassland biomass.
2：Sample Selection and Data Sources:
Field data were collected during the growing season of alpine grassland, using a stratified random sampling method at different geographical scales. Spectral information was recorded using an HR1024 spectrometer, and laboratory dry weights were measured.
3：List of Experimental Equipment and Materials:
HR1024 spectrometer for spectral information recording, HJ-1A hyperspectral imager (HIS) products, and MODIS NDVI images were used.
4：Experimental Procedures and Operational Workflow:
Spectral data processing included smooth denoising and averaging, calculation of spectral parameters, and regression analyses to establish biomass estimation models.
5：Data Analysis Methods:
Pearson correlation analysis, regression analysis, and model evaluation using root-mean-square error (RMSE), relative error, and average error index.
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