Finding feasible harvest zones in mountainous areas using integrated spatial multi-criteria decision analysis

Abstract

Terrain conditions, stand structure attributes, and environmental factors are important elements thatdetermine the success of timber harvests. Planning designs for timber harvesting projects must also bephysically feasible, environmentally acceptable, and economically viable and address potentially competingobjectives upfront in a multi-purpose planning effort. Under mountainous conditions involvinghighly variable and steep terrain, harvest planning is a particularly complex decision-making process.Here, quantitative (objective) information (e.g., stand volume) is jointly considered with qualitative (subjective)information (e.g., expert judgment of slope failure event and preference value of a certain stand) toarrive at a compromise plan that considers conflicting management objectives. The objective of this paperwas to evaluate the existing terrain conditions of a large management area to find zones in which harvestoperations can be conducted, assess which portions of the terrain can be harvested by different equipmentthat is available in the region, and locate landing sites for ground-based skidding operations. Thecriteria used in this study included quantitative and qualitative elements that were measured/evaluatedacross different scales. To address this complex decision-making process, we used an integrative approachthat combined spatial analyses with multiple-criteria decision analysis (SMCDA). Existing geospatial datawere combined with information obtained through pairwise evaluations of environmental, topographic,and stand structure elements to create maps in which the terrain was divided into zones of differentsuitability classes for timber harvests, placement of landing sites, and deployment of different harvestingsystems. The results and assessment of this case study indicate that the methodology has great potentialfor a more integrated policy, in particular, where multiple spatial objectives explicitly need to be takeninto consideration when solving complex forest-management problems in mountainous conditions. Onekey finding from this work that needs to be further explored involves efficient ways of incorporating thismethodology into traditional harvest scheduling models to better support the operational and tacticalphases of the timber harvesting.

Keywords

Timber harvesting; Spatial modeling; Decision support system; Machine-learning; Forest planning

Published in

Land Use Policy
2016, volume: 59, pages: 478-491

SLU Authors

• Ezzati, Sattar

  • Department of Forest Resource Management, Swedish University of Agricultural Sciences
    
  • Tarbiat Modares University

UKÄ Subject classification

Forest Science

Publication identifier

• DOI: https://doi.org/10.1016/j.landusepol.2016.09.020

Permanent link to this page (URI)

https://res.slu.se/id/publ/77434