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

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.

[1]  Eric Dinerstein,et al.  Beyond “Hotspots”: How to Prioritize Investments to Conserve Biodiversity in the Indo-Pacific Region , 1993 .

[2]  John R. Jensen,et al.  Introductory Digital Image Processing: A Remote Sensing Perspective , 1986 .

[3]  Stuart E. Marsh,et al.  Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery , 2005 .

[4]  R. Hall,et al.  Incorporating texture into classification of forest species composition from airborne multispectral images , 2000 .

[5]  Frédéric Achard,et al.  Mapping of the tropical forest cover of insular Southeast Asia from SPOT4-Vegetation images , 2003 .

[6]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[7]  T. Flannery Mammals of New Guinea , 1990 .

[8]  D. Roberts,et al.  Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales , 2005 .

[9]  T. Flannery Throwim Way Leg , 1998 .

[10]  Mary E. Martin,et al.  Determining Forest Species Composition Using High Spectral Resolution Remote Sensing Data , 1998 .

[11]  C. Tucker,et al.  NASA’s Global Orthorectified Landsat Data Set , 2004 .

[12]  G. Foody,et al.  Classification of tropical forest classes from Landsat TM data. , 1996 .

[13]  J. Alcorn Papua New Guinea : conservation needs assessment , 1993 .

[14]  Bryan F. J. Manly,et al.  Resource Selection by Animals , 1993, Springer Netherlands.

[15]  B. Manly,et al.  Resource selection by animals: statistical design and analysis for field studies. , 1994 .

[16]  William F. Laurance,et al.  Tropical wildlife corridors: use of linear rainforest remnants by arboreal mammals , 1999 .

[17]  J. Kirschner,et al.  The plant book , 1990, Folia Geobotanica et Phytotaxonomica.

[18]  J. Diamond Guns, Germs, and Steel: The Fates of Human Societies , 1999 .

[19]  J. L. Parra,et al.  Very high resolution interpolated climate surfaces for global land areas , 2005 .

[20]  W. T. Williams,et al.  The value of structural features in tropical forest typology , 1976 .

[21]  Russell G. Congalton,et al.  Assessing the accuracy of remotely sensed data : principles and practices , 1998 .

[22]  J. Conway,et al.  Evaluating ERS-1 SAR data for the discrimination of tropical forest from other tropical vegetation types in Papua New Guinea , 1997 .

[23]  Walter V. Reid,et al.  Conserving the World's Biological Diversity , 1990 .

[24]  Clyde W. Neu,et al.  A TECHNIQUE FOR ANALYSIS OF UTILIZATION- AVAILABILITY DATA' , 1974 .

[25]  Jean-Philippe Gastellu-Etchegorry,et al.  SPOT4 potential for the monitoring of tropical vegetation. A case study in Sumatra , 1999 .

[26]  S. Saulei Forest research and development in Papua New Guinea. , 1990 .

[27]  M. Ehlers,et al.  Review article: Thirty years of analysing and modelling avian habitat relationships using satellite imagery data: a review , 2005 .

[28]  M. Fladeland,et al.  Remote sensing for biodiversity science and conservation , 2003 .

[29]  David J. Mabberley,et al.  The Plant-Book , 1987 .

[30]  Douglas H. Johnson THE COMPARISON OF USAGE AND AVAILABILITY MEASUREMENTS FOR EVALUATING RESOURCE PREFERENCE , 1980 .

[31]  Nicholas J. Aebischer,et al.  Compositional Analysis of Habitat Use From Animal Radio-Tracking Data , 1993 .

[32]  N. Myers The primary source: Tropical forests and our future , 1984 .

[33]  S. Murai,et al.  Improvement of tropical vegetation mapping using a remote sensing technique: A case of Khao Yai National Park, Thailand , 2000 .

[34]  Edward O. Wilson,et al.  Our Diminishing Tropical Forests , 1988 .

[35]  Steven A. Sader,et al.  Migratory bird habitat monitoring through remote sensing , 1991 .

[36]  J. Tracey The Vegetation of the Humid Tropical Region of North Queensland. , 1983 .

[37]  G. Newell Australia's tree-kangaroos: current issues in their conservation , 1999 .