Assessment of Canopy Structure and Heterogeneity from Multi-angular CHRIS-PROBA Data

The spaceborne ESA-mission CHRIS-PROBA (Compact High Resolution Imaging SpectrometerProject for On-board Autonomy) provides hyperspectral and multi-angular data of selected terrestrial targets (Barnsley et al. 2004). For vegetated surfaces, the spectral information content of CHRIS data may yield the biochemical and biophysical properties of a vegetation canopy, while the directional component may deliever additional information on its canopy structure. Here, the multi-angular CHRIS observations are investigated and related to surface structure using the parametric Rahman-Pinty-Verstraete (RPV) model. RPV parameters, in particular the Minnaert function parameter k, are able to quantify the anisotropy of surface reflectance, which in turn is sensitive to the structure and heterogeneity of the observed surface. Thus to investigate the potential of multi-angular high spatial resolution data for delivering quantitative surface structure information the retrieved values of the k parameter are compared with proxies derived from detailed LIDAR observations describing the 3-D canopy structure of the target site. Posted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: https://doi.org/10.5167/uzh-97274 Published Version Originally published at: Koetz, Benjamin; Kneubühler, Mathias; Widlowski, Jean-Luc; Morsdorf, Felix; Schaepman, Michael E; Itten, Klaus I (2005). Assessment of canopy structure and heterogeneity from multi-angular CHRISPROBA data. In: 9th international symposium on Physical Measurements and Signatures in Remote Sensing (ISPMSRS), Beijing, China, 17 October 2005 19 October 2005, 76-78. Assessment of Canopy Structure and Heterogeneity from Multi-angular CHRIS-PROBA Data B. Koetz1, M. Kneubühler1, J.-L. Widlowski2, F. Morsdorf1, M. Schaepman3 and K. Itten1 1 Remote Sensing Laboratories (RSL), Dept. of Geography, University of Zurich, Switzerland, Email: [email protected] 2 Institute for Environment and Sustainability (IES), EC Joint Research Centre, Ispra (VA), Italy. 3 Centre for Geo-Information, Wageningen University and Research Centre, Wageningen, The Netherlands Abstract: The spaceborne ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer-Project for On-board Autonomy) provides hyperspectral and multi-angular data of selected terrestrial targets (Barnsley et al. 2004). For vegetated surfaces, the spectral information content of CHRIS data may yield the biochemical and biophysical properties of a vegetation canopy, while the directional component may deliever additional information on its canopy structure. Here, the multi-angular CHRIS observations are investigated and related to surface structure using the parametric RahmanPinty-Verstraete (RPV) model. RPV parameters, in particular the Minnaert function parameter k, are able to quantify the anisotropy of surface reflectance, which in turn is sensitive to the structure and heterogeneity of the observed surface. Thus to investigate the potential of multi-angular high spatial resolution data for delivering quantitative surface structure information the retrieved values of the k parameter are compared with proxies derived from detailed LIDAR observations describing the 3-D canopy structure of the target site. The spaceborne ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer-Project for On-board Autonomy) provides hyperspectral and multi-angular data of selected terrestrial targets (Barnsley et al. 2004). For vegetated surfaces, the spectral information content of CHRIS data may yield the biochemical and biophysical properties of a vegetation canopy, while the directional component may deliever additional information on its canopy structure. Here, the multi-angular CHRIS observations are investigated and related to surface structure using the parametric RahmanPinty-Verstraete (RPV) model. RPV parameters, in particular the Minnaert function parameter k, are able to quantify the anisotropy of surface reflectance, which in turn is sensitive to the structure and heterogeneity of the observed surface. Thus to investigate the potential of multi-angular high spatial resolution data for delivering quantitative surface structure information the retrieved values of the k parameter are compared with proxies derived from detailed LIDAR observations describing the 3-D canopy structure of the target site.