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|Title:||Abstract tree crowns in 3D radiative transfer models: Impact on simulated open-canopy reflectances|
|Authors:||WIDLOWSKI Jean-Luc; COTE Jean-Francois; BELAND Martin|
|Citation:||REMOTE SENSING OF ENVIRONMENT vol. 142 p. 155-175|
|Publisher:||ELSEVIER SCIENCE INC|
|Type:||Articles in periodicals and books|
|Abstract:||Three-dimensional (3D) radiative transfer models of vegetation canopies are increasingly used to study the reflective properties of specific land cover types and to interpret satellite-based remote sensing observations of such environments. In doing so, most 3D canopy reflectance models simplify the structural representation of individual tree crowns, for example, by using a single ellipsoidal envelope or a series of cubic volumes (known as voxels) to approximate the actual crown shape and the 3D distribution of scatterers therein. Often these tree abstractions ignore or simplify the woody architectures as well. Focusing on broad-leafed Savanna trees, this study investigates the impact that architectural simplifications may have on the fidelity of simulated satellite observations at the bottom-of-the-atmosphere for a variety of spatial resolutions, spectral bands, as well as, viewing and illumination geometries. As quality objective for the simulated bidirectional reflectance factors (BRFs) the typical uncertainty associated with vicarious calibration efforts is used, i.e., 5%. Our results indicate that the size of the voxel as well as the spectral, viewing, and illumination conditions drive the BRF bias at a given spatial resolution. The simulation of remote sensing data at medium spatial resolution is not affected by canopy abstractions except in the NIR for cases where woody structures are completely omitted. Here the BRF simulations of the abstract tree crowns exceeded the 5% tolerance limit even at spatial resolutions coarser than 100m. For high resolution satellite imagery, i.e. for nominal pixel sizes of 1×1 m2 or finer, BRF biases in excess of ±50% can occur within individual tree crowns and/or inside their shadows on the background. The sign of the local BRF bias is determined by the relative weight of the single-uncollided and single-collided BRF components.|
|JRC Directorate:||Sustainable Resources|
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