Canadian Forest Service Publications
Polygon decomposition with remotely sensed data: Rationale, methods and applications. 2001. Wulder, M.A.; Franklin, S.E. Geomatica 55 (1): 11-21.
Available from: Pacific Forestry Centre
Catalog ID: 18066
CFS Availability: Order paper copy (free)
Polygon decomposition refers to the process of analyzing previously-delineated polygon areas using ancillary digital information acquired from an independent source. The idea is to use those independent data, typically acquired through remote sensing, to provide insight into the internal characteristics of the polygonal area, often delineated using aerial photo-interpretation. The polygon or vector data are used as the context for the analysis of remotely-sensed or raster data. The polygonal data represent areas of generalization, but the remotely-sensed data can be used to make measurements or aggregate information in a meaningful way within those generalized areas. In essence, the polygonal information is a way of structuring or stratifying the remote-sensing information for analysis; another way to view this process is that remote-sensing data are a way of explaining the polygonal structure. The fusion of the raster and vector data allows for the augmentation of current information in the previously delineated polygon areas. The current information available from the remotely-sensed data may be physical properties, such as spectral reflectance values, or categorical properties, such as the result of an image classification or change detection procedure. In this paper we discuss polygon decomposition rationale, methods, and applications in research and application contexts.
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