First results of quantifying nonlinear mixing effects in heterogeneous forests: A modeling approach

Mixed satellite signals are traditionally modeled as linear combinations of the spectral signatures of its constituent components. Although nonlinearity has been shown to be significant for a variety of vegetation types, it is assumed to be negligible for most applications. We aim to assess the validity of the linear modeling assumption by making a quantitative analysis of the nature of multiple scattering effects in mixed forests. The effects of the spectral properties of the different species, structural differences and differences in tree height are evaluated. Virtual forest scenes and simulated hyperspectral satellite data were created through ray-tracing modeling using the Physically Based Ray-Tracer (PBRT) model. Results showed that both structure and the spectral properties influenced the nonlinear mixing behaviour, indicating that nonlinear unmixing models might be needed for forest cover mapping in heterogeneous forests.