Mapping foliar nutrition using WorldView-3 and WorldView-2 to assess koala habitat suitability

Huiying Wu*, Noam Levin, Leonie Seabrook, Ben D. Moore, Clive McAlpine

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Conservation planning and population assessment for widely-distributed, but vulnerable, arboreal folivore species demands cost-effective mapping of habitat suitability over large areas. This study tested whether multispectral data from WorldView-3 could be used to estimate and map foliar digestible nitrogen (DigN), a nutritional measure superior to total nitrogen for tannin-rich foliage for the koala (Phascolarctos cinereus). We acquired two WorldView-3 images (November 2015) and collected leaf samples from Eucalyptus woodlands in semi-arid eastern Australia. Linear regression indicated the normalized difference index using bands "Coastal" and "NIR1" best estimated DigN concentration (% dry matter, R 2 = 0.70, RMSE = 0.19%). Foliar DigN concentration was mapped for multi-species Eucalyptus open woodlands across two landscapes using this index. This mapping method was tested on a WorldView-2 image (October 2012) with associated koala tracking data (August 2010 to November 2011) from a different landscape of the study region. Quantile regression showed significant positive relationship between estimated DigN and occurrence of koalas at 0.999 quantile (R 2 = 0.63). This study reports the first attempt to use a multispectral satellite-derived spectral index for mapping foliar DigN at a landscape-scale (100s km 2 ). The mapping method can potentially be incorporated in mapping and monitoring koala habitat suitability for conservation management.

Original languageEnglish
Article number215
JournalRemote Sensing
Volume11
Issue number3
DOIs
StatePublished - 1 Feb 2019

Bibliographical note

Publisher Copyright:
© 2019 by the authors.

Keywords

  • Digestible nitrogen
  • Eucalyptus
  • Habitat mapping
  • Koalas
  • Remote sensing

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