Dry season mapping of savanna forage quality, using the hyperspectral Carnegie Airborne Observatory sensor

Nichola M. Knox, Andrew K. Skidmore, Herbert H.T. Prins, Gregory P. Asner, Harald M.A. van der Werff, Willem F. de Boer, Cornelis van der Waal, Hendrik J. de Knegt, Edward M. Kohi, Rob Slotow, Rina C. Grant

Research output: Contribution to journalArticlepeer-review

82 Scopus citations


Forage quality within an African savanna depends upon limiting nutrients (nitrogen and phosphorus) and nutrients that constrain the intake rates (non-digestible fibre) of herbivores. These forage quality nutrients are particularly crucial in the dry season when concentrations of limiting nutrients decline and non-digestible fibres increase. Using artificial neural networks we test the ability of a new imaging spectrometer (CAO Alpha sensor), both alone and in combination with ancillary data, to map quantities of grass forage nutrients in the early dry season within an African savanna. Respectively 65%, 57% and 41%, of the variance in fibre, phosphorus and nitrogen concentrations were explained. We found that all grass forage nutrients show response to fire and soil. Principal component analysis, not only reduced image dimensionality, but was a useful method for removing cross-track illumination effects in the CAO imagery. To further improve the mapping of forage nutrients in the dry season we suggest that spectra within the shortwave infrared (SWIR) region, or additional relevant ancillary data, are required.

Original languageEnglish (US)
Pages (from-to)1478-1488
Number of pages11
JournalRemote Sensing of Environment
Issue number6
StatePublished - Jun 15 2011
Externally publishedYes


  • ANN
  • Carnegie Airborne Observatory
  • Forage quality
  • Hyperspectral
  • Kruger National Park
  • Savannah

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences


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