SILVA - Faculty of Forest Science Research School

 

Considering Uncertainty in Forest Management Planning

The course is divided into 6 modules that address the different approaches to deal with uncertainty in forest management planning. The first section is a full-time module that provides an Introduction to Uncertainty in forest management, optimization in forestry, and forest management decision support systems. The other five modules will cover the following topics: Adaptive Forest Management, Monte Carlo simulation, Stochastic Programming, Stochastic Dynamic Programming, and Robust Optimization. During each module, there will be lectures, workshops, and teacher-led exercises. There will be seminars and guest lectures on forest management applications associated with each module and specific assignments linked to each of the learning outcomes.

Prerequisites
Students should be enrolled as PhD-students and have a master’s (or similar) in forest science or in mathematics, mathematical statistics, or engineer with interest in forest issues. In addition, the student must have basic knowledge of forest management planning and some experience with optimization methods used in forest planning e.g., linear programming

 

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