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Titolo:
Alternative priority models for forest planning on the landscape level involving multiple ownership
Autore:
Pykalainen, J; Pukkala, T; Kangas, J;
Indirizzi:
Univ Joensuu, Fac Forestry, FIN-80101 Joensuu, Finland Univ Joensuu Joensuu Finland FIN-80101 estry, FIN-80101 Joensuu, Finland Finnish Forest Res Inst, Kannus Res Stn, FIN-69101 Kannus, Finland FinnishForest Res Inst Kannus Finland FIN-69101 N-69101 Kannus, Finland
Titolo Testata:
FOREST POLICY AND ECONOMICS
fascicolo: 3-4, volume: 2, anno: 2001,
pagine: 293 - 306
SICI:
1389-9341(200107)2:3-4<293:APMFFP>2.0.ZU;2-5
Fonte:
ISI
Lingua:
ENG
Soggetto:
MANAGEMENT;
Keywords:
group decision making; forest management; private ownership planning; private forestry; landscape planning; forest policy;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Agriculture,Biology & Environmental Sciences
Citazioni:
31
Recensione:
Indirizzi per estratti:
Indirizzo: Pykalainen, J Univ Joensuu, Fac Forestry, POB 111, FIN-80101 Joensuu, Finland Univ Joensuu POB 111 Joensuu Finland FIN-80101 suu, Finland
Citazione:
J. Pykalainen et al., "Alternative priority models for forest planning on the landscape level involving multiple ownership", FOR POLICY, 2(3-4), 2001, pp. 293-306

Abstract

The study presents four ways to formulate a landscape level forest planning model for group planning using a heuristic optimization method called 'HERO'. The HERO method is composed of two primary steps: first, forest management goals are defined; then a management plan is sought to fulfill the defined goals. The planning models consider the landscape (whole area) and forest holdings as separate hierarchical levels. Within the planning models, each participant's forest management goals are defined using additive priority functions consisting of weighted sub-utility and/or achievement functions. Maximizing the achievement function minimizes the deviation from the target value for the corresponding goal variable. (i) The integrated top-down model uses achievement functions on the landscape level and sub-utility functions on the individual holding level; while GO the integrated bottom-up model uses achievement functions on the holding level and sub-utility functions on the landscape level. (i) The integrated utility maximization model consists of weighted sub-utility functions on both the landscape and the individual holding levels and GO the integrated regret minimization model usesachievement functions on both levels. The use of different priority modelswas illustrated in a case study, which consisted of four neighboring private land holdings. In general, the priority models worked in a logical way. Large deviations from the targets could be prevented by using achievement functions in the overall priority models. On the other hand, the differencesbetween the models were not very large, and the results of only one case cannot be generalized. It seems that all the alternative priority models might have use in different planning situations. However, interactive use of the models should be preferred. (C) 2001 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 08/04/20 alle ore 12:10:04