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 (fNPV) 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 (MCD43A4) data and field measured fNPV data to invert the fNPV model and evaluated the estimation effect of the model. The results show that the NPVIs based on MODIS data have a good correlation with fNPV. The correlations are as follows: DFI, SWIR32, NDTI, STI, NDI7, NDI5 and NDSVI. The DFI index inversion fNPV model has higher estimation accuracy. It can be applied to the rapid monitoring of large scale fNPV in typical steppe.
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Guoqi CHAI, Jingpu WANG, Guangzhen WANG, Liu HAN, Zhoulong WANG. Estimation of fractional cover of non-photosynthetic vegetation in typical steppe based on MODIS data. Remote Sensing for Land & Resources, 2019, 31(3): 234-241.
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2019, Vol. 31 
), 王光镇, 韩柳, 王周龙
