Strategic forest planning using AHP and TOPSIS in participatory environments

• Main Author: Nilsson, Hilma
• Format: Text
• Language: English
• Published: 2014
• Subjects: Forestry - General aspects; Forestry production; Northern Sweden
• Online Access: https://stud.epsilon.slu.se/7226/1/Nilsson_H_140901.pdf

When a decision is to be made on what long term strategic forest management plan to use, consideration must often be taken to multiple objectives. Such decisions are very complex and a promising approach to handle them is by Multiple Criteria Decision Analyses (MCDA). The study is based on the problem that the MCDA that have been implemented into forest management planning have only had capacity to compare and evaluate a limited number of management plans; which means that there is a risk the most suitable plan is missed. The aim with this study was to test the applicability of combining the MCDA tools: the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and the Analytic Hierarchy Process (AHP) for including consideration to multi-objectives into strategic forest management planning. The study was based on the process of creating and selecting a management plan, using Heureka PlanWise, suitable for all the major objectives found in the forest holdings of a municipality in northern Sweden. AHP was used to get the weights on the criteria defining the given objective, which then was implemented in TOPSIS in order to get the plans ranked depending on how well they fulfilled the given objective. The result showed that the combination of AHP and TOPSIS is practically easy to implement into a participatory forestry planning and that the full capacity of Heureka PlanWise’s ability to create numerous of management plans could come forward, which in turn reduced the chance that the optimal plan is missed. Den strategiska skogsskötseln i Sverige planeras ofta med en hundraårig planeringshorisont. För att den ska anses hållbar bör den ta hänsyn till andra mål än produktion, såsom sociala värden och rennäring. Heureka PlanVis är ett avancerat datasystem för långsiktiga skogliga analyser och med dess hjälp kan strategiska skötselplaner tas fram. Olika beslutsstöd för att välja den plan mest lämplig för de givna målen, t.ex. olika Multiple Criteria Decision Analyses (MCDA), har utvecklats och testats ...