Please use this identifier to cite or link to this item:
|Title:||Scale Independent Pattern Analysis|
|Authors:||VOGT Peter; OSTAPOWICZ Katarzyna; ESTREGUIL Christine|
|Citation:||Proceedings of the International Conference Landscape Ecology and Forest Management p. 170-171|
|Publisher:||Chinese Academy of Forestry|
|Type:||Articles in periodicals and books|
|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 Directorate:||Sustainable Resources|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.