STONE, Christine

Research interests

  • Operationally deployment of remote sensor systems (satellite/airborne/UAV platforms with passive (optical) and active (lidar) sensors for the assessment and monitoring of timber plantations and native forests.
  • Optimising remotely acquired, 3D point cloud data for plantation inventory.
  • Developing spatial products that inform the status and condition of native forests (e.g. for Montreal Process framework reporting).
  • Improved methodologies for the assessment and monitoring of forest and plantation health and condition

Background

Dr Christine Stone is Leader of the Forest Science team in NSW DPI Forestry. The DPI Forest Science team undertakes research and development in the areas of: forest ecology & sustainability; forest health & biosecurity; forest resource assessment; carbon in forests, wood products & bioenergy and forest monitoring. She is also a Senior Principal Research Scientist. She is recognised as a national authority on the application of remote sensing technologies for the assessment and monitoring of forests and timber plantations. In 2017 Christine was awarded the Institute of Foresters of Australia’s N.W. Jolly Medal, their most prestigious honour for outstanding service to the profession of forestry.

Qualifications

  • B.Agric.Sci. – University of Tasmania, 1980
  • MSc. (Applied Entomology) – Imperial College, London, 1982
  • PhD (Forest Entomology) – Macquarie University, 1990

Current and recently completed projects

  • Solutions for the optimal use of dense, remotely acquired data by forest growers. A National Institute for Forest Products Innovations funded project, commenced July 2019.
  • Optimising remotely acquired, dense point cloud data for plantation inventory. Funded by FWPA and concluded June 2018.
  • Deployment and integration of cost-effective high resolution remotely sensed data for the Australian forest industry. Funded by FWPA, concluded December 2017.

Recent publications

Stone, C. & Mohammed, C. (2017) Application of remote sensing technologies for assessing planted forests damaged by insect pests and fungal pathogens: A Review. Current Forestry Reports 3:75-92.

Haywood, A. & Stone, C. (2017) Estimating large area forest carbon stocks – A pragmatic design based strategy. Forests 8: Article 99, doi: 10.3390/f8040099.

Haywood, A., Thrum, K., Mellor, A. & Stone, C. (2018) Monitoring Victoria’s public forests: implementation of the Victorian Forest Monitoring Program. Southern Forests – a Journal of Forest Science 80:185-194.

Iqbal, I.A., Osborn J., Stone, C., Lucieer, A., Dell, M. & McCoull, C. (2018) Evaluating the robustness of point clouds from small format photography over a Pinus radiata plantation. Australian Forestry 81:162-176.

Pearse, G., Watt, M.S., Dash, J.P., Stone, C. & Caccamo, G. (2019) Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities.  Journal of Applied Earth Observations and Geoinformation.  78:341-351.

Dell, M., Stone, C., Osborn, J., Glen, M. et al. (2019) Detection of necrotic foliage in a young Eucalyptus pellita plantation using unmanned aerial vehicle RGB photography – a demonstration of concept. Australian Forestry 82:79-88.

Professional associations and activities

  • Institute of Foresters of Australia
  • Editorial Board member of Australian forestry

Fields of research

  • 070504 Forestry Management and Environment
  • 070505 Forestry Pests, Health and Diseases

Australian and New Zealand Standard Research Classification (ANZSRC)

Keyword/phrase list of research interests

  • Remote sensing of native forests and plantations
  • UAVs, Airborne laser scanning, satellites, Lidar, photogrammetry
  • Forest health and condition