학술논문

Quantitative analysis based on forest value maximization decision model
Document Type
Conference
Source
2023 2nd International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS) AIARS Artificial Intelligence and Autonomous Robot Systems (AIARS), 2023 2nd International Conference on. :72-76 Jul, 2023
Subject
Computing and Processing
Statistical analysis
Biological system modeling
Computational modeling
Scalability
Forestry
Programming
Mathematical models
Climate change
Felling plan
Marginal cost
Maximum Value
Language
Abstract
Global warming is one of the common environmental problems faced by mankind. Forest ecosystems have the function of sequestering carbon dioxide and become a key factor in slowing global warming. We considered how to address the greatest carbon sequestration in forests and how to balance environmental and economic benefits to make sound decisions. We incorporate the social optimal harvesting amount as a constraint into the maximum forest value decision model. In this model, we consider both the carbon sequestration value and economic value of forests to find a reasonable balance to make decisions. Finally, we calculated the optimal harvesting amount of poplar trees in a certain area of Xinjiang. Based on the above model, we have applied and promoted and planned a timeline to illustrate management strategies in different cycles.