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A region-based, graph-theoretic data model for the inference of second-order thematic information from remotely-sensed images

 

作者: STUART BARR,   MICHAEL BARNSLEY,  

 

期刊: International Journal of Geographical Information Science  (Taylor Available online 1997)
卷期: Volume 11, issue 6  

页码: 555-576

 

ISSN:1365-8816

 

年代: 1997

 

DOI:10.1080/136588197242194

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

A graph-theoretic data model, XRAG (eXtended Relational Attributed Graph), is described. The model and its associated data structure can be used to represent the structural properties (morphological and symbolic) of, and relations (spatial, topological, non-topological, quantitative and symbolic) between, discrete regions identified in a digital remotely-sensed image. The objective in developing this model is to allow second-order thematic information about the scene to be inferred from an analysis of these properties and relations. The paper briefly outlines the application of this model and an associated set of analytical techniques to infer land use from an initial land cover map derived from a digital remotely-sensed image.

 

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