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Multi-objective Forest Planning

  • Book
  • © 2002

Overview

Part of the book series: Managing Forest Ecosystems (MAFE, volume 6)

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About this book

Most of the scientific methods devised for forest planning support timber production ignoring the existence of forest functions other than wood production. Fortunately, the realisation that the forest planning methods available today do not correspond to the needs of today's forestry has activated forest researchers to develop and adopt new methodologies and approaches, which are specifically aimed at multi-objective situations. This book is about the quantitative approach to multi-objective forest planning. The emphasis is on topics that are rather new and not yet systematically applied in forest planning practice. The topics and methodologies discussed in this book include: measurement of preferences, multiple criteria decision analysis, use of GIS to support multi-objective forest management, heuristic optimization, spatial optimisation, and the measurement of non-wood forest outputs. By reading the book, a planning specialist, student or a researcher will get an insight into some of the current developments in forest planning research.

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Keywords

Table of contents (8 chapters)

Editors and Affiliations

  • University of Joensuu, Finland

    Timo Pukkala

Bibliographic Information

  • Book Title: Multi-objective Forest Planning

  • Editors: Timo Pukkala

  • Series Title: Managing Forest Ecosystems

  • DOI: https://doi.org/10.1007/978-94-015-9906-1

  • Publisher: Springer Dordrecht

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media Dordrecht 2002

  • Hardcover ISBN: 978-1-4020-1097-2Published: 31 December 2002

  • Softcover ISBN: 978-90-481-6207-9Published: 07 December 2010

  • eBook ISBN: 978-94-015-9906-1Published: 29 June 2013

  • Series ISSN: 1568-1319

  • Series E-ISSN: 2352-3956

  • Edition Number: 1

  • Number of Pages: VIII, 208

  • Topics: Forestry Management, Forestry, Operations Research/Decision Theory

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