Inversion of Masson pine forest LAI by multiple-perspective vegetation index

CHRIS/PROBA is a multiple-angle sensor providing hyper-spectral data with 17 m×17 m spatial resolution that can be applied for data inversion of vegetation canopy structure parameters, such as tree height and leaf area index (LAI). We used a four-scale geometrical optics model to simulate anisotropy distribution regulation of the normalized difference vegetation index (NDVI) of a Pinus massoniana (Masson pine) forest canopy. By extracting the red and near infrared characteristic spectral bands from the 18 bands in CHRIS, a new multi-angle normalized hotspot-dark-spot difference vegetation index (NHDVI) was applied to the estimation of the LAI of Pinus massoniana forest using CHRIS data. The results showed that:(1) Compared with the NDVI and soil adjusted vegetation index (SAVI), NHDVI well integrated the spectral information and angle information with the ground measured LAI, and the coefficient of determination reached 0.7278; (2) The LAI was calculated by statistical regression of NHDVI-LAI. The correlation between the LAI and the measured values was 0.8272, significantly higher than that of SAVI, and the root mean square error (RMSE) was 0.1232. Thus, these findings indicate that angular information is important for improving the retrieval accuracy of LAI.