Title: Scale Independent Pattern Analysis
Authors: VOGT PeterOSTAPOWICZ KatarzynaESTREGUIL Christine
Citation: Proceedings of the International Conference Landscape Ecology and Forest Management p. 170-171
Publisher: Chinese Academy of Forestry
Publication Year: 2008
JRC Publication N°: JRC49178
URI: http://research.eeescience.utoledo.edu/lees/IUFRO/2008MTG/
http://publications.jrc.ec.europa.eu/repository/handle/JRC49178
Type: Contributions to Conferences
Abstract: Morphological spatial pattern analysis (MSPA) is a mathematical framework extending the existing pattern analysis tools in landscape ecology to a generic, unsupervised, and scale-independent description of raster image components. Key improvements include the separation of internal and external features and the detection of structural connectivity. The principles are briefly reviewed and the resulting feature classes explained. In addition, the method is flexible since variable scales of analysis are allowed on a given input map. The generic nature of this methodology is used as a reference base for pattern analysis at different scales. The impact of the scales of the input data and of the analysis, and the combination of both is evaluated for a series of forest maps. We demonstrate the reliable spatial pattern analysis at any given scale and investigate the information contained in the behaviour of pattern classes across the series of scales. A frequency map summarizes these findings and gives new insights for the understanding of forested landscapes. The proposed technology provides a simple but powerful framework for a pattern assessment at any scale as well as across scales. The reliable detection and evaluation of forest structure and its scale dependent dynamics are a prerequisite for a better understanding of processes related to biodiversity and pattern - species interaction at different spatial scales.
JRC Institute:Institute for Environment and Sustainability

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