天山北坡草地盖度高光谱遥感估算

以天山北坡乌鲁木齐县甘沟乡为研究区,利用美国SVC HR-768便携式光谱仪采集25块样方的高光谱数据,并测定对应样方中草地盖度,分析草地盖度与原始光谱、一阶微分光谱和高光谱特征变量之间的相关关系;采用回归统计的方法,基于高光谱位置变量、高光谱面积变量和高光谱植被指数变量构建草地盖度的估测模型,并进行模型精度评价。结果表明,研究区草地盖度与植被冠层光谱反射率相关性较强的波段范围为354-704、1 420-1 481和1 904-2 512nm;基于一阶微分光谱和高光谱植被指数构建的估测模型能更好地反演草地盖度。通过模型检验,确定基于560nm的光谱一阶微分模型y=-384.153x+72.096可作为草地盖度的最优估测模型,模型均方根误差为7.344%,估算精度为90.343%。

Estimating grassland coverage based on hyperspectral remote sensing in the northern Tianshan Mountains

By taking the Gan'gou Township in Urumqi County on the northern slope of the Tianshan Mountains as the study area,and using an America SVC HR-768 portable spectroradiometer,we collected hyperspectral data and corresponding grassland coverage data at 25 sites.Using these data,we analysed the correlation between grassland coverage and the original spectrum and the first-order differential spectrum and the hyperspectral characteristic variables.We also constructed a hyperspectral estimation model of grassland coverage by using regression methods based on the hyperspectral position variables,the hyperspectral area variables,and the hyperspectral vegetation index variables,and evaluated the accuracy of simulation models.The results showed that there was a strong correlation between grassland coverage and vegetation canopy reflectance in the spectral ranges of 354-704 nm,1 420-1 481 nm,and 1 904-2 512 nm;the estimation models based on first-order differential spectrum and hyperspectral vegetation index variables can invert grassland coverage better.Model testing indicated that the first-derivate model based on 560 nm y=-384.153x+72.096 can be considered to be the best estimation model of grassland coverage,for which the root mean square error was 7.344% and the estimation accuracy was 90.343%.