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Proceedings Paper

Geostatistical framework for conflation of heterogeneous geospatial data
Author(s): Jinping Zhang; Deren Li; Jingxiong Zhang
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Paper Abstract

The term conflation is used as a superset of all kinds of integral approaches to combining heterogeneous geospatial data, aiming for synergism in geospatial information processes, thus added values in resultant information products. A coherent strategy for conflation is built upon an evaluation of spatial data models, which include discrete objects that are geo-referenced by position and associated with some qualitative and/or quantitative attributes, and fields that are continuous or discrete in terms of the scale of measurement. Regardless of whether positional errors or errors in fields are concerned, they can be conceived of as being realizations of regionalized random variables. Therefore, multivariate geostatistics provides a straightforward framework for conflation of spatial data. Scale is an important metric in spatial data, which can be handled in co-kriging procedures by incorporating block-support variograms derived from point-support variograms, functioning as either downscaling or upscaling depending on the interaction between the existing data and the information or analysis required. The methods for scale-dependent manipulation and cross-scale integration of multi-source data will be described, followed by some discussions.

Paper Details

Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679038 (14 November 2007); doi: 10.1117/12.750942
Show Author Affiliations
Jinping Zhang, Wuhan Univ. (China)
Deren Li, Wuhan Univ. (China)
Jingxiong Zhang, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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