HallHayBouchardEtAl2004

Référence

Hall, O., Hay, G.J., Bouchard, A., Marceau, D.J. (2004) Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation. Landscape Ecology, 19(1):59-76.

Résumé

Complex systems, such as landscapes, are composed of different critical levels of organization where interactions are stronger within levels than among levels, and where each level operates at relatively distinct time and spatial scales. To detect significant features occurring at specific levels of organization in a landscape, two steps are required. First, a multiscale dataset must be generated from which these features can emerge. Second, a procedure must be developed to delineate individual image-objects and identify them as they change through scale. In this paper, we introduce a framework for the automatic definition of multiscale landscape features using object-specific techniques and marker-controlled watershed segmentation. By applying this framework to a high-resolution satellite scene, image-objects of varying size and shape can be delineated and studied individually at their characteristic scale of expression. This framework involves three main steps: 1) multiscale dataset generation using an object-specific analysis and upscaling technique, 2) marker-controlled watershed transformation to automatically delineate individual image-objects as they evolve through scale, and 3) landscape feature identification to assess the significance of these image-objects in terms of meaningful landscape features. This study was conducted on an agro-forested region in southwest Quebec, Canada, using IKONOS satellite data. Results show that image-objects tend to persist within one or two scale domains, and then suddenly disappear at the next, while new image-objects emerge at coarser scale domains. We suggest that these patterns are associated to sudden shifts in the entire image structure at certain scale domains, which may correspond to critical landscape thresholds.

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@ARTICLE { HallHayBouchardEtAl2004,
    AUTHOR = { Hall, O. and Hay, G.J. and Bouchard, A. and Marceau, D.J. },
    TITLE = { Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation },
    JOURNAL = { Landscape Ecology },
    YEAR = { 2004 },
    VOLUME = { 19 },
    PAGES = { 59-76 },
    NUMBER = { 1 },
    NOTE = { 09212973 (ISSN) Cited By (since 1996): 4 Export Date: 26 April 2007 Source: Scopus CODEN: LAECE doi: 10.1023/B:LAND.0000018371.43447.1f Language of Original Document: English Correspondence Address: Hall, O.; Dept. Phys. Geogr. Quaternary Geol.; Stockholm University SE-106 91 Stockholm, Sweden; email: ola.hall@humangeo.su.se References: Allen, T.F.H., Starr, T.B., (1982) Hierarchy Perspective for Ecological Complexity, , University of Chicago Press, Chicago, Illinois, USA; Beucher, S., Bilodeau, M., Yu, X., Road segmentation by watersheds (sic) algorithms (1990) Proceedings of the Pro-art Vision Group PROMETHEUS Workshop, pp. 1-24. , Sophia-Antipolis, France, April; Beucher, S., The watershed transformation applied to image segmentation (1992) 10th Conference on Signal and Image Processing in Microscopy and Microanalysis, 6, pp. 299-314. , 16-19 Sept. 1991, Cambridge, UK. 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    ABSTRACT = { Complex systems, such as landscapes, are composed of different critical levels of organization where interactions are stronger within levels than among levels, and where each level operates at relatively distinct time and spatial scales. To detect significant features occurring at specific levels of organization in a landscape, two steps are required. First, a multiscale dataset must be generated from which these features can emerge. Second, a procedure must be developed to delineate individual image-objects and identify them as they change through scale. In this paper, we introduce a framework for the automatic definition of multiscale landscape features using object-specific techniques and marker-controlled watershed segmentation. By applying this framework to a high-resolution satellite scene, image-objects of varying size and shape can be delineated and studied individually at their characteristic scale of expression. This framework involves three main steps: 1) multiscale dataset generation using an object-specific analysis and upscaling technique, 2) marker-controlled watershed transformation to automatically delineate individual image-objects as they evolve through scale, and 3) landscape feature identification to assess the significance of these image-objects in terms of meaningful landscape features. This study was conducted on an agro-forested region in southwest Quebec, Canada, using IKONOS satellite data. Results show that image-objects tend to persist within one or two scale domains, and then suddenly disappear at the next, while new image-objects emerge at coarser scale domains. We suggest that these patterns are associated to sudden shifts in the entire image structure at certain scale domains, which may correspond to critical landscape thresholds. },
    KEYWORDS = { Complex system Critical landscape threshold Feature detection Hierarchy IKONOS Marker-controlled watershed segmentation Multiscale Object-specific analysis Object-specific upscaling Scale domain data set landscape ecology landscape structure },
    OWNER = { brugerolles },
    TIMESTAMP = { 2007.12.04 },
}

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