Research
CURRENT RESEARCH - - contact me directly for latest info.
Research Program:
PhD
Title:
The use of Remote sensing in habitat modelling of fragmented environments
Key Words:
Remote Sensing, habitat modelling, Scale, ecology, landcover
Project Aims:
* Development of a framework to assess the impact of scale dependent factors on the classification landcover.
* Assess the impact of variability in landcover maps on the development of habitat suitability models.
Project Summary:
This project investigates the use of high spatial resolution remote sensing in habitat modelling, particularly in fragmented environments. Fragmented natural habitats, such as peri-urban areas, are some of the most difficult to model due to the lack of accurate up-to-date maps of an appropriate scale. Remote sensing is often heralded as a solution to this mapping problem; however image objects may be spectrally and spatially similar and confound mapping particularly at high spatial resolutions. Fragmented environments are spatially complex with habitat patches varying in size from median strips (~10m2) to large vegetation remnants contained within national parks (100km2).
Depending on the remote sensing data, classification technique and class description used to produce maps of environmental variables, there may be large differences in the final product. The resulting map might vary in the extent, patchiness and accuracy of classified areas. The framework developed for this study will allow the objective investigation of the application of high resolution imagery for habitat modelling. The development of this framework allows researchers to compare different sensor resolutions, environments and the final mapped products. The framework is based on an understanding of the interaction between different scale-dependent factors, positional accuracy and classification techniques and their effects on, classification accuracy, change in patch area and patchiness of classes. It was found that there was a difference in the accuracy, patchiness and total area classified area cover when the scale dependent factors such as pixel size were changed. The study demonstrated that landcover maps used to create habitat models are subjective and the product of the classification technique and sensor used. Furthermore there tends to be greater variability in the classification outcome of fragmented landscapes.
PUBLICATIONS
Journals
Southwell, D. M., A. Lechner, T. Coates, and B. A. Wintle. (in press). The sensitivity of population viability analysis to uncertainty about habitat requirements: Implications for the management of the endangered southern brown bandicoot (Isoodon obesulus) Conservation Biology.
Book Chapters
Lechner, A. M., S. D. Jones, and S. A. Bekessy. (in press). A STUDY ON THE IMPACT OF SCALE DEPENDENT FACTORS ON THE CLASSIFICATION OF LANDCOVER MAPS in A. Stein, J. Shi, and B. Wietske, editors. Quality Aspects in Spatial Data Mining. Chapman and Hall/CRC Press.
Books
Buxton, M., G. Tieman, S. Bekessy, T. Budge, A. Butt, M. Coote, A. Lechner, D. Mercer, D. O’Neill, and C. Riddington 2007. Change and Continuity in Peri-urban Australia, Peri-Urban Case Study: Bendigo Corridor,. RMIT University, Melbourne.
Conferences
Lechner, A. M., S. D. Jones, and S. A. Bekessy. 2007. DEVELOPMENT OF A FRAMEWORK TO ASSESS THE IMPACT OF SCALE DEPENDENT FACTORS ON THE CLASSIFICATION OF LANDCOVER MAPS. Proceedings of the 5th International symposium on Spatial Data Quality ISSDQ 2007, Modelling qualities in space. ITC, Enschede, The Netherlands.
Jones, S. D., K. Sheffield, K. J. Reinke, N. Miura, and A. M. Lechner. 2007. Remote Sensing Native Vegetation Condition. Asian Conference on Remote Sensing, Kuala Lumpur
MASTER'S THESIS
Population viability analysis of the Southern Brown Bandicoot in the Greater Melbourne area. Click here for more info