I am a lecturer and researcher in GIS and remote sensing in the Centre for Spatial Information Science. In 2000, I graduated with a Masters in Physical Geography from Utrecht University in the Netherlands. In 2004, I finished my PhD on visualisation and classification of satellite imagery.
Career Summary
During my M.Sc. in Physical Geography, I specialised in Geographical Information Science (GIS), dynamical modelling and remote sensing. The Department of Physical Geography at Utrecht University in the Netherlands is internationally renowned for its GIS modelling expertise and education. For my M.Sc. thesis, I focused on modelling the surface thermal heat-balance, using hyper-spectral remote sensing imagery. During my practical period at the Joint Research Centre in Italy, I further developed my dynamical modelling skills by application to river flooding for two main river catchments in Europe, the Meuse and Oder.
In 2000, I started my Ph.D. at the International Institute for Geo-Information Science and Earth Observation (ITC) in the Netherland, focussing on modelling and visualising uncertainty in remote sensing segmentation and classification. During my PhD, I developed a software tool for texture-based segmentation of satellite images for identification of land cover objects. Another component of the tool is the use of interactive visualisation to improve awareness and understanding of uncertainty in remote sensing image processing. The software tool (Parbat) is available on the Internet for public use at http://www.parbat.net. I have published several papers in peer-refereed journals (see list of publications) and I have presented my work at over fifteen conferences and workshops. I was awarded my PhD degree in October 2004. More information about this research and my background can be found on my website, http://www.lucieer.net.
From June 2004 until present, I have been a lecturer in GIS and remote sensing within the Centre for Spatial Information Science in the School of Geography and Environmental Studies, University of Tasmania. My research at the University of Tasmania continues to focus on texture-based segmentation, fuzzy classification, and interactive visual exploration of remotely sensed imagery. Since December 2004, I have also worked for the Australian Antarctic Division to strengthen the role of remote sensing in Antarctic and sub-Antarctic research. My main focus in this position was to analyse high-resolution satellite imagery for mapping and monitoring vegetation on sub-Antarctic Heard and Macquarie Island. Recently, I have successfully applied for a research grant involving funding for Quickbird imagery of Macquarie Island to map sub-Antarctic vegetation. Additionally, I have successfully applied for acquisition time of the European Space Agency’s Proba/CHRIS sensor over Heard Island in 2006/2007. I aim to actively pursue research funding for remote sensing research and (inter)national collaboration in the future.
Community engagement
I am a member of the Spatial Science Institute (SSI) in Australia. In addition, I am a member of the Tasmanian SSI committee and the national remote sensing and photogrammetry working group for the SSI.
I have an interest in web design and I try to engage the community in my research through my websites. My personal website http://www.lucieer.net disseminates information on my research projects. Furthermore, I have developed a software tool, Parbat, for processing and visualisation of satellite imagery. This tool is freely and publicly available at http://www.parbat.net. The CenSIS website http://www.utas.edu.au/spatial provides a lot of interesting information about the spatial industry and research projects in spatial sciences.
Research Interests
Satellite images provide a rich source of information for studying the Earth surface. One of my particular interests is in the application of pattern recognition algorithms to remote sensing. Pattern recognition techniques aim to simulate human vision to extract features from satellite images; examples include vegetation and landform classification. In mapping natural features, we often tend to draw sharp or discrete boundaries between classes. This is often unrealistic as transition zones between classes (i.e. one vegetation class changing into another: forest, shrub, grassland) often occur in natural areas. My research focuses on using fuzzy techniques to quantify uncertainty related to these transition zones. My current area of interest is in using these novel techniques to map vegetation and vegetation change on sub-Antarctic Heard Island and Macquarie Island.
Additionally, I am interested in using advanced and interactive visualisation techniques to provide more insight into patterns in a satellite image. Visualisation tools can help to explain the results of a complex pattern recognition algorithm in a more accessible and appealing way. The field of remote sensing is exciting to work in as technology is changing rapidly requiring rapid development of new techniques and tools for analysis and information extraction. It is great to combine research with fancy images and interesting areas! For more information, please visit my website: http://www.lucieer.net
Projects
Research:
- Applications in remotely sensed vegetation mapping and monitoring on sub-Antarctic islands
- Classification of sub-Antarctic vegetation from high-resolution satellite imagery on Heard Island and Macquarie Island
- Assessing the impact of rabbit grazing on Macquarie Island using satellite imagery
- Pattern recognition: segmentation and classification of remotely sensed imagery with a focus on texture and uncertainty
- Information visualization for data mining of remotely sensed imagery
- Advanced image processing techniques in remote sensing
Teaching
I teach second and third year undergraduate units in GIS and remote sensing. I am also actively involved in supervision of honours and postgraduate research projects. I am coordinating and teaching the following units:
UnitsSelected Publications:- Lucieer, A., Stein A., and Fisher, P., 2005, 'Texture-based segmentation of high-resolution remotely sensed imagery for identification of fuzzy objects', International Journal of Remote Sensing, 26(14), pgs. 2917-2936
- Lucieer, A. and Stein, A., 2005, 'Texture-based landform segmentation of LiDAR imagery', International Journal of Applied Earth Observation and Geoinformation, 6(3-4), pgs. 261-270
- Lucieer, A., 2004, 'Uncertainties in Segmentation and their Visualisation, PhD Thesis', International Institute for Geo-Information Science and Earth Observation (ITC) and University of Utrecht, The Netherlands, printed by ITC, URL: http://www.lucieer.net, ISBN: 90-6164-225-6
- Lucieer, A., Fisher, P., and Stein, A., 2004, 'Texture-based Segmentation of Remotely Sensed Imagery to Identify Fuzzy Coastal Objects ', GeoDynamics, edited by G. Foody and P. Atkinson, CRC Press LLC, pgs. 87-102
- Lucieer, A. and Kraak, M. J., 2004, 'Alpha-shapes for visualizing irregular shaped class clusters in 3D feature space for classification of remotely sensed imagery, Proceedings of SPIE', The International Society for Optical Engineering, Visualization and Data Analysis, San Jose, 5295, pgs. 201-211
- Lucieer, A., and Kraak, M.J., 2004, 'Interactive and visual fuzzy classification of remotely sensed imagery for exploration of uncertainty
', International Journal of Geographical Information Science , Vol. 18, Nr. 5, pgs. 491--512
- Lucieer, A., and Stein, A., 2002, 'Existential uncertainty of spatial objects segmented from satellite sensor imagery
', IEEE Transactions on Geoscience and Remote Sensing, Vol. 40, Nr. 11, pgs. 2518--2521
Full Publication List Current and Supervised Project/s:
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