NDLI: Information representation and integration of multiple sets of spatial geoscience data

Content Provider	IEEE Xplore Digital Library
Author	Moon, W.M. So, C.S.
Copyright Year	1995
Description	Author affiliation: Manitoba Univ., Winnipeg, Man., Canada (Moon, W.M.; So, C.S.)
Abstract	Earth science and exploration data have characteristic features in both temporal and spatial space which are distinct on the terrestrial spectrum. These data sets can be either continuous or discrete. Recently there have been a number of studies based on information representation theory and AI/expert system techniques for processing and interpretation of multiple sensor spatial data sets with both global and regional coverage. There are in general two approaches in spatial data fusion and interpretation of the results; one based on specific rules, including geological and geophysical principles, and a more direct data driven approach. In the paper, some of the basic mathematical relationships often utilized in a data driven spatial information fusion methods are reviewed. Uncertainties in the hypotheses and experimental errors can also be handled and processed using same formalism, if the proper information representation technique is carefully chosen. To quantify the basic information contained in each data layer, and to accurately represent the information, it is important to understand statistical meaningfulness of each data set on the terrestrial spectrum for the final integration using currently popular GISs. In this paper, the basic concepts in preprocessing of geoscience data and information representation techniques, including the fuzzy logic, evidential belief function, and Bayesian probability, are discussed.
Starting Page	2141
Ending Page	2144
File Size	404907
Page Count	4
File Format	PDF
ISBN	0780325672
DOI	10.1109/IGARSS.1995.524130
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-07-10
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information representation Geoscience Artificial intelligence Expert systems Sensor phenomena and characterization Sensor systems Geology Uncertainty Fuzzy logic Bayesian methods
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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