Journal
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
Volume 57, Issue 5-6, Pages 327-345Publisher
ELSEVIER
DOI: 10.1016/S0924-2716(02)00162-4
Keywords
complex systems theory; fractal net evolution approach; image-objects; multiscale object-specific analysis
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Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene, and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement. (C) 2003 Elsevier Science B.V. All rights reserved.
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