  Although many spectral unmixing models have been developed to address
spectral variability caused by variable incident illuminations, the mechanism
of the spectral variability is still unclear. This paper proposes an unmixing
model, named illumination invariant spectral unmixing (IISU). IISU makes the
first attempt to use the radiance hyperspectral data and a LiDAR-derived
digital surface model (DSM) in order to physically explain variable
illuminations and shadows in the unmixing framework. Incident angles, sky
factors, visibility from the sun derived from the LiDAR-derived DSM support the
explicit explanation of endmember variability in the unmixing process from
radiance perspective. The proposed model was efficiently solved by a
straightforward optimization procedure. The unmixing results showed that the
other state-of-the-art unmixing models did not work well especially in the
shaded pixels. On the other hand, the proposed model estimated more accurate
abundances and shadow compensated reflectance than the existing models.
