A scale-space primer for exploring and quantifying complex landscapes

Over the last two decades, the scale-space community has developed into a reputable field in computer vision, yet its nontrivial mathematics (i.e. group invariance, differential geometry and tensor analysis) limit its adoption by a larger body of researchers and scientists, whose interests in multis...

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Bibliographic Details
Published in:Ecological modelling 2002-07, Vol.153 (1), p.27-49
Main Authors: Hay, G.J., Dubé, P., Bouchard, A., Marceau, D.J.
Format: Article
Language:English
Subjects:
Animal and plant ecology
Animal, plant and microbial ecology
Biological and medical sciences
Blob-feature detection
Complex systems
Fundamental and applied biological sciences. Psychology
General aspects
General aspects. Techniques
Landscape patterns
Methods and techniques (sampling, tagging, trapping, modelling...)
Multiscale analysis
Scale-space
Synecology
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Summary:Over the last two decades, the scale-space community has developed into a reputable field in computer vision, yet its nontrivial mathematics (i.e. group invariance, differential geometry and tensor analysis) limit its adoption by a larger body of researchers and scientists, whose interests in multiscale analysis range from biomedical imaging to landscape ecology. In an effort to disseminate the ideas of this community to a wider audience we present this non-mathematical primer, which introduces the theory, methods, and utility of scale-space for exploring and quantifying multi-scale landscape patterns within the context of Complex Systems theory. In addition, we suggest that Scale-Space theory, combined with remote sensing imagery and blob-feature detection techniques, satisfy many of the requirements of an idealized multiscale framework for landscape analysis.
ISSN:0304-3800
1872-7026
DOI:10.1016/S0304-3800(01)00500-2