Inversion of a coupled canopy–atmosphere model using multi-angular top-of-atmosphere radiance data: A forest case study Valérie C.E. Laurent a, ⁎, Wout Verhoef b , Jan G.P.W. Clevers a , Michael E. Schaepman c a Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, P.O. Box 47, 6700 AA Wageningen, The Netherlands b Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands c Remote Sensing Laboratories, University of Zurich, Winterthurerstr. 190, CH-8057 Zurich, Switzerland abstract article info Article history: Received 9 March 2011 Received in revised form 23 May 2011 Accepted 29 May 2011 Available online 25 June 2011 Keywords: Top-of-atmosphere Radiative transfer CHRIS/PROBA Forest variable estimation Multi-angular Since the launch of sensors with angular observation capabilities, such as CHRIS and MISR, the additional potential of multi-angular observations for vegetation structural and biochemical variables has been widely recognised. Various methods have been successfully implemented to estimate forest biochemical and biophysical variables from atmospherically-corrected multi-angular data, but the use of physically based radiative transfer (RT) models is still limited. Because both canopy and atmosphere have an anisotropic behaviour, it is important to understand the multi-angular signal measured by the sensor at the top of the atmosphere (TOA). Coupled canopy–atmosphere RT models allow linking surface variables directly to the TOA radiance measured by the sensor and are therefore very interesting tools to use for estimating forest variables from multi-angular data. We investigated the potential of TOA multi-angular radiance data for estimating forest variables by inverting a coupled canopy–atmosphere physical RT model. The case study focussed on three Norway spruce stands located at the Bily Kriz experimental site (Czech Republic), for which multi-angular CHRIS and field data were acquired in September 2006. The soil–leaf–canopy RT model SLC and the atmospheric model MODTRAN4 were coupled using a method allowing to make full use of the four canopy angular reflectance components provided by SLC. The TOA radiance simulations were in good agreement with the spectral and angular signatures measured by CHRIS. Singular value decompositions of the Jacobian matrices showed that the dimensionality of the variable estimation problem increased from 3 to 6 when increasing the number of observation angles from 1 to 4. The model inversion was conducted for two cases: 4 and 7 variables. The most influential parameters were chosen as free variables in the look-up tables, namely: vertical crown cover (Cv), fraction of bark material (fB), needle chlorophyll content (needleCab), needle dry matter content (needleCdm) for the 4-variable case, and additionally, tree shape factor (Zeta), dissociation factor (D), and needle brown pigments content (needleCs) in the 7-variable case. All angular combinations were tested, and the best estimates were obtained with combinations using two or three angles, depending on the number of variables and on the stand used. Overall, this case study showed that, although making use of its full potential is still a challenge, TOA multi-angular radiance data do have a higher potential for variable estimation than mono-angular data. © 2011 Elsevier Inc. All rights reserved. 1. Introduction Forest environments cover about 30% of the Earth surface (FAO, 2006) and play an important role in the carbon and water cycles. Projection scenarios based on dynamic global vegetation models can therefore benefit from accurate information about forest variables such as leaf area index (LAI), chlorophyll content and canopy cover. These variables can be efficiently monitored using satellite data, which provide regular and spatially continuous coverage. The reflectance of most land surfaces, including forests, depends on the acquisition (illumination-target-observation) geometry. This an- isotropy is often regarded as an undesired effect which needs to be corrected before using the image (Bacour et al., 2006; Schaaf et al., 2002). Another view is that the reflectance anisotropy contains additional information about the target, and that consequently multi-angular data have more potential for estimating surface variables than mono-angular data (Asner et al., 1998; Diner et al., 1999; Liang et al., 2000; Schaepman, 2007). In the last decades, several space-borne instruments have been launched to sample the radiation field of land surfaces in both spectral and angular dimensions, in a near-simultaneous way (e.g. CHRIS, MISR, POLDER). For forest applications, multi-angular data have been used for Remote Sensing of Environment 115 (2011) 2603–2612 ⁎ Corresponding author. Tel.: + 31 317 481917; fax: + 31 317 419000. E-mail addresses: valerie.laurent@wur.nl (V.C.E. Laurent), verhoef@itc.nl (W. Verhoef), jan.clevers@wur.nl (J.G.P.W. Clevers), michael.schaepman@geo.uzh.ch (M.E. Schaepman). 0034-4257/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2011.05.016 Contents lists available at ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse