Issues related to the detection of boundaries |
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Authors: | Fortin M.-J. Olson R.J. Ferson S. Iverson L. Hunsaker C. Edwards G. Levine D. Butera K. Klemas V. |
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Affiliation: | (1) School of Resource and Environmental Management, Simonfraser University, Burnabay, B.C., Canada, V5A 1SB;(2) Environmental Sciences Division, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6407, USA;(3) Applied Biomathematics, 100 North Country Road, Setauket, NY 11733-1345, USA;(4) USDA Forest Service, 359 Main Road, Delaware, OH 43015, USA;(5) USDA Forest Service, 2081 E. Sierra Avenue, Fresno, CA 93710, USA;(6) Centre de recherche en géomatique, Université Laval Sainte Foy, Québec, G1K 7P4, Canada;(7) Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6274, USA;(8) DynaCorp, 2000 Edmund Halley Drive, Reston, VA 20191-3436, USA;(9) Center for Remote Sensing, University of Delaware, 107A Robinson Hall, Newark, DE 19716-3501, USA |
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Abstract: | Ecotones are inherent features of landscapes, transitional zones, and play more than one functional role in ecosystem dynamics. The delineation of ecotones and environmental boundaries is therefore an important step in land-use management planning. The delineation of ecotones depends on the phenomenon of interest and the statistical methods used as well as the associated spatial and temporal resolution of the data available. In the context of delineating wetland and riparian ecosystems, various data types (field data, remotely sensed data) can be used to delineate ecotones. Methodological issues related to their detection need to be addressed, however, so that their management and monitoring can yield useful information about their dynamics and functional roles in ecosystems. The aim of this paper is to review boundary detection methods. Because the most appropriate methods to detect and characterize boundaries depend of the spatial resolution and the measurement type of the data, a wide range of approaches are presented: GIS, remote sensing and statistical ones. |
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Keywords: | environmental change GIS landscape ecology modeling remote sensing riparian statistics wetland |
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