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Computing information gain for spatial data support

Published: 05 November 2008 Publication History

Abstract

Widespread use of GPS devices and explosion of remotely sensed geospatial images along with cheap storage devices has resulted in vast amounts of data. More recently, with the advent of wireless technology, a large number of sensor networks have been deployed to monitor many human, biological and natural processes. This poses a challenge in many data rich application domains. The problem now is how best to choose the datasets to solve specific problems. Some of the datasets may be redundant and their inclusion in analysis may not only be time consuming, but may lead to erroneous conclusions. We propose the concept of data support as the basis for efficient, cost-effective and intelligent use of geospatial data in order to reduce uncertainty in the analysis and consequently in the results. Data support is defined as the process of determining the information utility of a data source to help decide which one to include or exclude to improve cost-effectiveness in existing data analysis. In this article we use mutual information as the basis of computing data support. The concept of mutual information is defined in information theory as a measure to compute information gain or loss between two disjoint datasets. We use this to compute the optimal datasets in specific applications. The effectiveness of the approach is demonstrated using an application in the hydrological analysis domain.

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Cover, T. M., Thomas, J. A. (2005). Elements of Information Theory, Second Edition. John Wiley & Sons, Inc., Hoboken, New Jersey.
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Fu, L., Samal, A., Soh, L.-K. (2008). Techniques for Computing Fitness of Use (FoU) for Time Series Datasets with Applications in the Geospatial Domain. In Geoinformatica, Vol. 12, Issue 1, pp. 91--115.
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Hunter, G. (1998). Managing Uncertainty in GIS, NCGIA Core Curriculum in GIScience, http://www.ncgia.ucsb.edu/giscc/units/u187/u187_f.html, posted February 03, 1998.
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cover image ACM Conferences
GIS '08: Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
November 2008
559 pages
ISBN:9781605583235
DOI:10.1145/1463434
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 05 November 2008

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  1. information gain/loss
  2. spatial data support

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