Determination of optimized forest road route using BIM software with a precise forestry approach

In this study, the potential of optimization tools to generate a high number of alternatives on the BIM model and the ability of the CRITIC method to generate criteria weights are examined. The contribution of precision forestry tools such as LiDAR and GIS to the BIM model and result accuracy is also emphasized. The ability of users to determine their own criteria and make evaluations in an easy interface increases the efficiency of decision-making processes. This method provides a user-friendly solution for forest road planning. An existing forest road and seven alternative routes to this road were defined in BIM environment based on LiDAR-based SAM source for a forest road in IUC Forestry Faculty Education Research Forest. These alternatives were weighted by CRITIC method in terms of technical, ecological and social aspects and ranked by MOORA method. While the existing road is the most advantageous in terms of cost, Alternative 4 is the most costly option. In terms of technical evaluation, Alternative 3 was found to be the most suitable, and in terms of ecological impacts, Alternative 3 was also the most favorable. Alternative 3 performed best in terms of social impacts. With the weighted average method, the criteria were evaluated with 25% equal weight and Alternative 3 was determined as the most suitable alternative with the lowest weighted score. Although the existing road is advantageous in terms of cost and environmental aspects, it ranked third in terms of overall performance. Alternative 4 received the highest weighted score and was considered the most disadvantageous alternative. The results emphasize the importance of balanced consideration of multifaceted criteria in road alignment selection. The balanced performance of Alternative 3 in terms of cost, technical, ecological and social aspects highlights this route as a sustainable and economic solution. This study makes important contributions to the efficient use of resources and minimization of environmental impacts.