The Impact of NPV on the Spectral Parameters in the Yellow-Edge, Red-Edge and NIR Shoulder Wavelength Regions in Grasslands

Even though research has shown that the spectral parameters of yellow-edge, red-edge and NIR (near-infrared) shoulder wavelength regions are able to estimate green cover leaf area index (LAI), a large amount dead materials in grasslands challenges accuracy their estimation using hyperspectral remote sensing. However, exact impact vegetation on these remains unclear. Therefore, we evaluated influences by comparing normalized difference indices (NDVI) including common red valley at 670 nm NDVI extracted new statistical method. This method, based concept segmented linear regression, was developed extract calculate automatically from hyper-spectra. To fully understand (i.e., consider full coverage combinations vegetation, bare soil), both situ measured simulated hyper-spectra were analyzed. The LAI those also evaluated. results show that: (i) without considering influence soil, decreases slope red-edge, NDVI, while increases yellow-edge; (ii) characteristics disappear when exceeds 67%; (iii) result blue shift position; (iv) accurate extraction position enhances reduces NDVI; (v) significantly drops 72.3–74.5% (variation among indices).