Merging the Minnaert- k Parameter With Spectral Unmixing to Map Forest Heterogeneity With CHRIS/PROBA Data

• Published in: IEEE transactions on geoscience and remote sensing 2010-11, Vol.48 (11), p.4014-4022
• Main Authors: Verrelst, Jochem, Clevers, Jan G P W, Schaepman, Michael E
• Format: Article
• Language: English
• Subjects: Anisotropic magnetoresistance; Canopies; canopy; classification; Compact High Resolution Imaging Spectrometer (CHRIS); cover; forest heterogeneity mapping; Forests; Heterogeneity; High-resolution imaging; hyperspectral data; Image sampling; imaging spectroscopy; land; Mathematical models; Merging; misr; multi-angular; Onboard; Optical surface waves; reflectance; reflectance anisotropy; Reflectivity; rpv model; Space vehicles; Spatial resolution; Spectra; Spectral lines; Spectroscopy; surface; Surface waves; vegetation indexes
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2010.2047400

The Compact High Resolution Imaging Spectrometer (CHRIS) mounted onboard the Project for Onboard Autonomy (PROBA) spacecraft is capable of sampling reflected radiation at five viewing angles over the visible and near-infrared regions of the solar spectrum with high spatial resolution. We combined the spectral domain with the angular domain of CHRIS data in order to map the surface heterogeneity of an Alpine coniferous forest during winter. In the spectral domain, linear spectral unmixing of the nadir image resulted in a canopy cover map. In the angular domain, pixelwise inversion of the Rahman-Pinty-Verstraete (RPV) model at a single wavelength at the red edge (722 nm) yielded a map of the Minnaert-k parameter that provided information on surface heterogeneity at a subpixel scale. However, the interpretation of the Minnaert-k parameter is not always straightforward because fully vegetated targets typically produce the same type of reflectance anisotropy as non-vegetated targets. Merging both maps resulted in a forest cover heterogeneity map, which contains more detailed information on canopy heterogeneity at the CHRIS subpixel scale than is possible to realize from a single-source optical data set.