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Forest Ecosystems 2022, 9(1): 100001 https://doi.org/10.1016/j.fecs.2022.100001
Research Article | Open Access | Issue | Published: 25 February 2022

Two-level optimization approach to tree-level forest planning

Show Author's Information Yusen Suna,  Xingji Jina( ),  Timo Pukkalaa,b( ),  Fengri Lia
Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin, 150040, Heilongjiang, China
University of Eastern Finland, P.O. Box 111, 80101, Joensuu, Finland
Keywords:
Multi-objective optimization, Simulated annealing, Differential evolution, Heuristic-optimization, Individual-tree detection
Cite this article:
Sun Y, Jin X, Pukkala T, et al. Two-level optimization approach to tree-level forest planning. Forest Ecosystems, 2022, 9(1): 100001. https://doi.org/10.1016/j.fecs.2022.100001
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Abstract Full text About this article
Background

Laser scanning and individual-tree detection are used increasingly in forest inventories. As a consequence, methods that optimize forest management at the level of individual trees will be gradually developed and adopted.

Results

The current study proposed a hierarchical two-level optimization method for tree-level planning where the cutting years are optimized at the higher level. The lower-level optimization allocates the trees to the cutting events in an optimal way. The higher-level optimization employed differential evolution whereas the lower-level problem was solved with the simulated annealing metaheuristic. The method was demonstrated with a 30 ​m ​× ​30 ​m sample plot of planted Larix olgensis. The baseline case maximized the net present value as the only management objective. The solution suggested heavy thinning from above and a rotation length of 62 years. The baseline problem was enhanced to mixed stands where species diversity was used as another management objective. The method was also demonstrated in a problem that considered the complexity of stand structure, in addition to net present value. The objective variables that were used to measure complexity were the Shannon index (species diversity), Gini index (tree size diversity), and the index of Clark and Evans, which was used to describe the spatial distribution of trees. The article also presents a method to include natural advance regeneration in the optimization problem and optimize the parameters of simulated annealing simultaneously with the cutting years.

Conclusions

The study showed that optimization approaches developed for forest-level planning can be adapted to problems where treatment prescriptions are required for individual trees.


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About this article

Two-level optimization approach to tree-level forest planning

Show Author's information Yusen Suna, Xingji Jina( ), Timo Pukkalaa,b( ), Fengri Lia
Key Laboratory of Sustainable Forest Ecosystem Management - Ministry of Education, School of Forestry, Northeast Forestry University, Harbin, 150040, Heilongjiang, China
University of Eastern Finland, P.O. Box 111, 80101, Joensuu, Finland

Abstract

Background

Laser scanning and individual-tree detection are used increasingly in forest inventories. As a consequence, methods that optimize forest management at the level of individual trees will be gradually developed and adopted.

Results

The current study proposed a hierarchical two-level optimization method for tree-level planning where the cutting years are optimized at the higher level. The lower-level optimization allocates the trees to the cutting events in an optimal way. The higher-level optimization employed differential evolution whereas the lower-level problem was solved with the simulated annealing metaheuristic. The method was demonstrated with a 30 ​m ​× ​30 ​m sample plot of planted Larix olgensis. The baseline case maximized the net present value as the only management objective. The solution suggested heavy thinning from above and a rotation length of 62 years. The baseline problem was enhanced to mixed stands where species diversity was used as another management objective. The method was also demonstrated in a problem that considered the complexity of stand structure, in addition to net present value. The objective variables that were used to measure complexity were the Shannon index (species diversity), Gini index (tree size diversity), and the index of Clark and Evans, which was used to describe the spatial distribution of trees. The article also presents a method to include natural advance regeneration in the optimization problem and optimize the parameters of simulated annealing simultaneously with the cutting years.

Conclusions

The study showed that optimization approaches developed for forest-level planning can be adapted to problems where treatment prescriptions are required for individual trees.

Keywords: Multi-objective optimization, Simulated annealing, Differential evolution, Heuristic-optimization, Individual-tree detection

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Published: 25 February 2022
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