Added value of multiangular measurements for estimating forest variables from the top of the atmosphere using coupled radiative transfer models

Abstract

Numerous studies have demonstrated the higher information content of multiangular reflectance data that can be used to improve the estimation of variables for surfaces having strong directional properties such as forests. Only a few studies, however, used physically- based radiative transfer (RT) models, and they were based on atmospherically-corrected data. The objective of this study was to investigate the potential of multi-angular top-of-atmosphere (TOA) radiance data for estimating surface variables using a coupled canopy-atmosphere model. The study area consisted of three Norway spruce stands located in the Czech Republic for which field data and a multi-angular set of four CHRIS/PROBA images were collected in September 2006. The coupled SLC (Soil-Leaf- Canopy) - MODTRAN model provided good simulations of the spectral and angular signatures measured by CHRIS. Local sensitivity analyses were performed to help with the model inversion. The singular values of the Jacobian matrix showed that the dimensionality of the estimation problem increased from 3 to 6 when increasing the number of angles from 1 to 4. One LUT was built for each stand, using the 7 most influential parameters: vertical crown cover, fraction of bark, tree shape factor, dissociation factor, and needle chlorophyll, dry matter, and brown pigments contents. All angular combinations were tested for estimating the variables. The best results were obtained when using two or three angles. The results show that although multi-angular TOA radiance data do have a higher potential than mono-angular data, it is still difficult to make full use of the information they contain for estimating forest variables