Discrimination of dominant forest types for Matschie's tree kangaroo conservation in Papua New Guinea using high-resolution remote sensing data

  • Authors:
  • J. A. Stabach;L. Dabek;R. Jensen;Y. Q. Wang

  • Affiliations:
  • The Woods Hole Research Center, Falmouth, MA 02540, USA;Tree Kangaroo Conservation Program, Conservation Department, Woodland Park Zoo, Seattle, WA 98103, USA;-;Laboratory for Terrestrial Remote Sensing, Department of Natural Resources Science, University of Rhode Island, Kingston, RI 02881, USA

  • Venue:
  • International Journal of Remote Sensing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Matschie's tree kangaroos (Dendrolagus matschiei) are arboreal marsupials endemic to the Huon Peninsula in Papua New Guinea (PNG). Primarily because of an increase in hunting pressure and loss of habitat from agricultural expansion, D. matschiei is currently listed as endangered by the International Union for the Conservation of Nature. This paper reports the results of our study to compare the capabilities of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Satellite Pour l'Observation de la Terre (SPOT)-4 multispectral image data at discriminating dominant forest types at a remote research location in PNG. Nearest-neighbour vegetation plots were established from July to August 2004 to obtain detailed information about the vegetative communities and guide class assignments. Forests were separated into four distinct habitat types with Dacrydium nidulum dominant forests being the most widespread and the most accurately classified. The comparative results indicated that Landsat-7 and Spot-4 had similar classification accuracies but the results were low because of the complex structure and heterogeneity of the forest communities and the limited spatial/spectral resolutions of the satellite data sources. This research provides an improved result compared to past research and provides detailed information towards the future conservation of Matschie's tree kangaroo habitat in PNG.