Shape-based unmixing for vegetation mapping

Spectral mixture analyses (SMA) is often used as a tool to map complex/mixed (semi-)natural ecosystems. Yet, the performance of SMA, which traditionally uses the amplitude-based RMSE as the objective function, is often hampered by the high spectral similarity among co-occurring plant species. Experiments, based on ray-tracing simulations, in situ measured reflectance data and AVIRIS imagery demonstrated the added value of implementing shape-based error metrics in the unmixing of forests and orchards. The approach allowed to highlight the subtle spectral differences among co-occurring plant species resulting in an overall improvement of species specific mapping (i. e. decrease in MSE ≈ 40%).

[1]  P. Vitousek,et al.  Remote analysis of biological invasion and biogeochemical change. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Jin Chen,et al.  A Quantitative Analysis of Virtual Endmembers' Increased Impact on the Collinearity Effect in Spectral Unmixing , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Jin Chen,et al.  Generalization of Subpixel Analysis for Hyperspectral Data With Flexibility in Spectral Similarity Measures , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[4]  Margaret E. Gardner,et al.  Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models , 1998 .

[5]  Greg Humphreys,et al.  Physically Based Rendering: From Theory to Implementation , 2004 .

[6]  Roberta E. Martin,et al.  Invasive species detection in Hawaiian rainforests using airborne imaging spectroscopy and LiDAR. , 2008 .

[7]  W. Verstraeten,et al.  The impact of common assumptions on canopy radiative transfer simulations: A case study in Citrus orchards , 2009 .

[8]  W. Verstraeten,et al.  Nonlinear Hyperspectral Mixture Analysis for tree cover estimates in orchards , 2009 .

[9]  Pol Coppin,et al.  Endmember variability in Spectral Mixture Analysis: A review , 2011 .

[10]  Pol Coppin,et al.  3D modeling of light interception in heterogeneous forest canopies using ground-based LiDAR data , 2011, International Journal of Applied Earth Observation and Geoinformation.