Shape-based unmixing for vegetation mapping

L. Tits, B. Somers, W. De Keersmaecker, G. P. Asner, J. Farifteh, P. Coppin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 amplitudebased 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 overal improvement of species specific mapping (i:e: decrease in MSE ≈ 40%).

Original languageEnglish (US)
Title of host publication2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012
PublisherIEEE Computer Society
ISBN (Print)9781479934065
DOIs
StatePublished - Jan 1 2012
Externally publishedYes
Event2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012 - Shanghai, China
Duration: Jun 4 2012Jun 7 2012

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
ISSN (Print)2158-6276

Conference

Conference2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012
CountryChina
CityShanghai
Period6/4/126/7/12

Keywords

  • Hyperspectral
  • Spectral Mixture Analysis
  • forests
  • orchards
  • spectral similarity

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Tits, L., Somers, B., De Keersmaecker, W., Asner, G. P., Farifteh, J., & Coppin, P. (2012). Shape-based unmixing for vegetation mapping. In 2012 4th Workshop on Hyperspectral Image and Signal Processing, WHISPERS 2012 [6874222] (Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing). IEEE Computer Society. https://doi.org/10.1109/WHISPERS.2012.6874222