呼伦贝尔典型草原区植物生长旺季地上干物质量估算的地面光谱模型

为促进地面高光谱遥感在草地估产方面的应用,采用美国ASD公司生产的Fieldspec3光谱仪,于2009年7月下旬在呼伦贝尔典型草原区进行了高光谱遥感地面观测试验.运用单变量线性、非线性和逐步回归分析方法,建立植物生长旺季归一化植被指数(NDVI)与地上干物质量(ANPP)间的地面光谱模型.结果表明,基于判定系数(R2)判断,线性函数和指数函数拟合较理想,R2分别达到0.7295和0.7203.误差分析表明,标准误差(SE)最大的是对数函数,其SE为24.82gm2;最小的是幂函数,其SE为22.63gm2.平均误差系数(MEC)最大的是对数函数,其MEC为0.2497;指数函数最小,其MEC为0.1932.综合分析后,选用一元线性回归方程作为呼伦贝尔典型草原区的植物生长旺季最优地面光谱模型:ANPP=406.08NDVI-101.64,其R2为0.7295,SE为23.61gm2,MEC为0.2209,P0.001.

Ground Spectral Model for Estimating Above-Ground Net Primary Productivity at the Peak of Growing Season on Typical Steppe, Hulunbeier, Inner Mongolia, China

To improve the research and application of hyperspectral data of remote sensing to estimate grassland biomass, an ASD Fieldspec 3 spectroradiometer was used for spectral measurements of the Hulunbeier grassland, Inner Mongolia, China, in late July, 2009. Ground spectral models were built to estimate the Above-ground Net Primary Productivity (ANPP) at the peak of the growing season from the Normalized Difference Vegetation Index (NDVI) measured in the field. One-sample linear regression, nonlinear regression and stepwise analysis methods were used to assess relationships between ANPP and NDVI. Based on the coefficient of determination (R~2), linear model (R~2=0.7295) and exponential model (R~2=0.7203) were better than others. Error analysis shows that the logarithmic equation has the biggest standard error of the prediction (SE=24.82 g/m~2) and coefficient of mean error (MEC =0.2497), the power equation has the smallest SE (SE=22.63 g/m~2), and the exponential equation has the smallest MEC (MEC =0.1932). After considering all factors, a linear equation between ANPP and NDVI (ANPP=406.08NDVI-101.64,R~2=0.7295, SE=23.61 g/m~2, MEC=0.2209, P<0.001) was selected and used for the study area at the peak of the growing season.