Masters research project

MSc student: Steven Keady
Supervisors: Prof. John O'Halloran, Dr. Sandra Irwin & Dr. Barry O'Sullivan
Funder: EPA STRIVE Programme (2007-2013).

Project Description:
This project investigated the feasibility of using Terrestrial Laser Scanning to provide information on structural forest attributes and investigated the relationship between this and forest biodiversity measured using traditional biodiversity surveys of plans, invertebrates and birds. We found good agreement between field and Terrestrial Laser Scanning measures of forest structure, including Diameter at Breast Height and Deadwood.We used data mining to predict each of five biodiversity measures based on the physical descriptions obtained of the forests using laser scanning  and found that biodiversity, in terms of species richness and abundance, can be predicted using measures of forest structure derived from Terrestrial Laser Scanning.

Terrestrial Laser Scanning:
Terrestrial Laser Scanning was developed to capture detailed, 3-D information about an object’s dimensions, spatial positioning, texture and colour and is widely used in architectural, engineering and industrial measurement. In recent years it has been adapted for use in the forest industry where it is now commonly used for taking measurements from standing timber in a non-destructive manner in order to inform optimal harvest decision-making and reduce waste. The Irish company TreeMetrics Ltd. who coolaborated on this project, and are at the cutting edge of this field, have developed a fully automated laser scanning system for pre-harvest timber measurement. The data collected using laser scanning has a wide range of other potential applications in forests outside those concerned with timber production including monitoring of carbon sequestration, and the measurement of structural characteristics of forest stands related to biodiversity.

These images of a commercial Sitka spruce plantation (above) and a semi-natural woodland (below)
were compiled using data collected by Terrestrial Laser Scanning.‌

Publications:

• Keady, S., O'Sullivan, B., Irwin, S. and O’Halloran, J. 2010. LASERBIO: The Applicability of Terrestrial Laser Scanning in Forest Biodiversity Assessment. EPA National Research Conference, 23 June 2010, Croke Park Conference Centre, Dublin. Poster Presentation.
• O’Sullivan, B., Keady, S., Keane, E., Irwin, S. and O’Halloran, J. 2010. Data Mining for Biodiversity Prediction in Forests. Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence, 289-294.
• O’Sullivan, B., Keady, S., Keane, E., Irwin, S. and O’Halloran, J. 2010. Data Mining for Biodiversity Prediction in Forests. 7th International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. Springer Lecture Notes in Computer Science 6140.
• Keady, S. 2011. Ground Based LiDAR for Forest Biodiversity Assessment. Unpublished MSc thesis, University College Cork.

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