4.7 Article

Retrieving structural and chemical properties of individual tree crowns in a highly diverse tropical forest with 3D radiative transfer modeling and imaging spectroscopy

Journal

REMOTE SENSING OF ENVIRONMENT
Volume 211, Issue -, Pages 276-291

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2018.04.023

Keywords

Hyperspectral remote sensing; DART; Functional traits; Model inversion; Tree species classification; Tropical forest

Funding

  1. Sao Paulo Research Foundation (FAPESP) [2013/11.589-5, 2015/50484-0, 2016/24977-1]
  2. Coordination for the Improvement of Higher Education Personnel (CAPES) [3424/2015-04]
  3. Brazilian National Council for Scientific and Technological Development (CNPq) [303563/2008-7, 301190/2013-5]
  4. HyperTropik project (TOSCA program grant of the French Space Agency, CNES)

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Spatial and temporal information on the structural and chemical properties of tropical forest canopies are key to understanding ecosystem processes. However, such information is usually limited to field studies performed at the plot level (similar to 1 ha). The combination of imaging spectroscopy with physically based radiative transfer (RT) models holds great promise for generalizing and extrapolating insights from plot-based studies to whole landscapes. Here, we tested the capacity of a simplified 3D RT approach to retrieve the structural and chemical traits of individual tree crowns (ITCs) from a highly diverse tropical forest. We first produced two datasets called measured and simulated. The measured dataset was composed of ITC reflectance extracted from sunlit imaging spectroscopy pixels. The simulated dataset was produced using a look-up-table approach and the discrete anisotropic radiative transfer (DART) model. We then compared the simulated and measured reflectances of ITCs in terms of shape difference by computing the spectral angle. The results showed small disagreements between the simulated and measured reflectances. Such differences impacted neither the spectral variability nor the spectral regions recognized as useful for species discrimination, showing that the spectral angle was a suitable measure of spectral similarity. Simulation robustness was assessed by comparing model parameters obtained by inversion to imaging spectroscopy vegetation indices and the proportion of non-photosynthetic vegetation (NPV), green photosynthetic vegetation (GV) and shade estimated within ITCs. DART canopy structural parameters were related to NPV (R-2 = 0.71), GV (R-2 = 0.78) and shade (R-2 = 0.55). DART canopy foliar parameters such as chlorophyll and carotenoids were related to the ratio of TCARI/OSAVI (R-2 = 0.80) indices and the simple ratio between reflectances at 515 nm and 570 nm (R-515/R-570) (R-2 = 0.54), respectively. Species-related differences in NPV, GV and shade were explained by variations in crown architectural characteristics. The simulation framework employed in this study can be applied to retrieve structural and chemical traits of ITCs from other areas in which high-resolution imaging spectroscopy data are available.

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