【摘要】 非光合植被(non-photosynthetic vegetation,NPV)在草原生态系统中扮演了重要角色,影响着生态系统的碳、水和能量的流动与循环。定量掌握草原非光合植被覆盖度(fractional cover of non-photosynthetic vegetation,f NPV)信息对草地资源的科学有效利用以及生态环境保护具有重要意义。以内蒙古自治区锡林郭勒典型草原为研究区,运用线性回归分析方法,建立基于MODIS (MCD43A4)数据构建的多种非光合植被指数(non-photosynthetic vegetation indices,NPVIs)和野外实测f NPV数据的反演模型,并对模型的估算结果进行验证。研究结果表明,基于MODIS数据构建的NPVIs与f NPV的相关性较好,相关性依次为:DFI,SWIR32,NDTI,STI,NDI7,NDI5及NDSVI; DFI指数反演f NPV模型的估算精度较高,可用于典型草原地区大范围f NPV的快速监测。更多还原

【Abstract】 Non-photosynthetic vegetation( NPV) is an important component of grassland ecosystem,which affects the flow and cycle of carbon,water and energy in the ecosystem. It is of great significance to quantitatively grasp the fractional cover of non-photosynthetic vegetation( f NPV) information for the scientific and effective utilization of grassland resources and the protection of the ecological environment. Taking the typical steppe of Xilingol in Inner Mongolia as the research area and using the regression analysis method,the authors used a variety of non-photosynthetic vegetation indices( NPVIs) based on MODIS( MCD43 A4) data and field measured f NPV data to invert the f NPV model and evaluated the estimation effect of the model. The results show that the NPVIs based on MODIS data have a good correlation with f NPV. The correlations are as follows: DFI,SWIR32,NDTI,STI,NDI7,NDI5 and NDSVI. The DFI index inversion f NPV model has higher estimation accuracy. It can be applied to the rapid monitoring of large scale f NPV in typical steppe.更多还原