Development of Higher-Order Model for Nonlinear Interactions in Hyperspectral Data of Mangrove Forests

The present article analyses the accuracy of application of higher-order nonlinear interaction models on hyperspectral data to identify mangrove mixtures present in the Sunderbans Delta - a World Heritage Site in West Bengal, India. It is observed that intra-species interaction between similar mangrove species (interaction between the same type of end-members) in a homogeneous mangrove stand is more accurately modelled by the linear-quadratic model and hence results in more accurate fractional abundance estimations after unmixing when compared with linear-unmixing models. Specifically, we observe that quadratic models provide more accurate estimates than linear and bilinear models for the study area (Henry Island of Sunderbans), which is mostly dominated by pure and mixed mangrove species of Avicennia marina, Excoecaria agallocha, Avicennia alba, Phoenix paludosa, Avicennia officinalis, Ceriops decandra, Bruguiera cylindrica and Aegialitis. In this study, the quadratic nonlinear model successfully characterizes the interaction of endmember mixtures comprising E. agallocha, A. officinalis, B. cylindrica and A. alba in the study area.