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On some aspects of data integration techniques with environmental applications
Author(s) -
Sinha Bikas K.,
Shah Kirti R.
Publication year - 2003
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.595
Subject(s) - multiple criteria decision analysis , judgement , ranking (information retrieval) , rank (graph theory) , computer science , context (archaeology) , data integration , phrase , environmental pollution , operations research , management science , data mining , environmental science , information retrieval , mathematics , environmental protection , artificial intelligence , geography , political science , engineering , archaeology , combinatorics , law
Multiple Criteria Decision Making (MCDM) is a popular phrase used to describe situations where there is a need for integration of the results of different studies to make an overall judgement. Among the highest priorities towards socioeconiomic development around the world is the Environmental Protection Policy (EPP), and environmental assessment is a key to EPP. In the context of environmental studies, data integration techniques are very appealing and have wider applicability. It is well known that land, air and water are the three sources for determination of the extent of pollution of different regions. The purpose of MCDM is to rank the regions wrt all the sources taken together. For any individual source of pollution, it is trivial to rank the regions from best to worst. However, the problem of integration becomes non‐trivial in most cases since the regions do not lend themselves to the same pattern of ranking wrt different sources. In this article we examine critically the performance of two popular composite indices (CI) and suggest some alternatives. Copyright © 2003 John Wiley & Sons, Ltd.