草地生物量的高光谱遥感估算模型

为了推进高光谱遥感在草地生理生化参数定量化方面的研究与应用，从冠层尺度上估算草地生物量，该文选用美国ASD公司的ASD FieldSpec Pro FRTM光谱仪，对内蒙古自治区锡林郭勒盟的天然草地进行高光谱遥感地面观测。在进行天然草地地上生物量与原始光谱和高光谱特征变量相关分析的基础上，将观测数据分成两组：一组观测数据作为训练样本，运用单变量线性、非线性和逐步回归分析方法，建立生物量高光谱遥感估算模型；另一组观测数据作为检验样本，进行精度检验。结果表明：生物量与高光谱吸收特征参数变量的分析中，以840、1132、1579、1769和2012 nm等5个原始高光谱波段反射率为变量的逐步回归估算方程为最佳模型，模型标准差为0.404 kg/m²，估算精度为91.6%，说明可以利用高光谱反射率数据，从冠层上对草地生物量进行量化。

Hyperspectral remote sensing estimation models for the grassland biomass

In order to improve the research and application of hyperspectral remote sensing in the quantification of biophysical indices and biochemical indices of grassland, and estimate the grassland biomass at the canopy scale, an ASD FieldSpec Pro FRTM spectroradiometer was used for the spectral measurements of natural grassland in Xilin Gol League, Inner Mongolia. First, correlation between original spectral, hyperspectral feature variables and above-ground biomass of natural grassland was analysed. Second, the basic experiment data including biomass and canopy reflectance of natural grassland were classified into two groups. One group was used as the training sample to build the regression models with the one-sample linear method, the nonlinear method and the stepwise analysis method; the other group was used as the testing sample to test the precision of regression models. Results show that the stepwise regression estimation model using the five hypeespectral reflectances of 840, 1132, 1579, 1769 nm and 2012 nm was the best, the estimation standard deviation was 0.404 kg/m², the estimation precision was 91.62%. The results of this paper indicate that the grassland biomass can be estimated at the canopy level using the hyperspectral reflectance.