Providing useful insights on the use of Multi-Criteria Decision Analysis (MCDA) in natural resource management, this book examines a number of empirical applications for several countries and a variety of natural resources. It is shown that using MCDA in the management of water, forestry, wetland and other natural resources can substantially improve the design and implementation of natural resource and environmental policies. Stakeholder involvement is also an important determinant of successful resource management and MCDA provides a useful and effective framework for getting stakeholders involved in resource management decisions. Using Multi-Criteria Decision Analysis in Natural Resource Management gives in-depth analysis of the potential problems in applying these techniques, including difficulties eliciting required information, lack of suitable measures for environmental variables and the need to develop innovative methods to simplify the use of MCDA.

chapter 1|10 pages

Role of Multi-Criteria Decision Making in Natural Resource Management

ByGamini Herath, Tony Prato

chapter 2|30 pages

Analysis of Forest Policy Using Multi-attribute Value Theory

ByJayanath Ananda, Gamini Herath

chapter 3|20 pages

Comparing Riparian Revegetation Policy Options using the Analytic Hierarchy Process

ByM.E. Qureshi and S.R. Harrison

chapter 7|24 pages

Fuzzy Multiple Attribute Evaluation of Agricultural Systems

ByLeonie A. Marks, Elizabeth G. Dunn

chapter 8|34 pages

Multi-Criteria Decision Support for Energy Supply Assessment

ByBram Noble

chapter 9|28 pages

Seaport Development in Vietnam: Evaluation Using the Analytic Hierarchy Process

ByTran Phuong Dong, David M. Chapman

chapter 10|14 pages

Valuing Wetland Aquatic Resources Using the Analytic Hierarchy Process

ByProcess Premachandra Wattage, Simon Mardle

chapter 11|12 pages

Multiple Attribute Evaluation for National Park Management

ByTony Prato

chapter 12|6 pages

The Future of MCDA in Natural Resource Management: Some Generalizations

ByGamini Herath, Tony Prato