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Academic Journal of Computing & Information Science, 2022, 5(9); doi: 10.25236/AJCIS.2022.050903.

Research and Application of Carbon Storage Prediction and Management Evaluation Model


Hanlin Cui, Junye Jiang, Xue Ren

Corresponding Author:
Hanlin Cui

School of Electrical and Informtion Engineering, Wuhan Institute of Technology, Wuhan, China


Firstly, based on CASA model and LULC data, this paper establishes a carbon sequestration and oxygen release service model. By estimating the carbon storage in different regions, the effect of influencing factors on carbon sequestration is obtained. Establish a differential equation to fit the amount of carbon dioxide storage, and compare the impact of different management methods on carbon storage. The results showed that under the constraints of UN indicators, the weight of the impact of reasonable forest breeding on carbon sequestration was 0.401, higher than other indicators. Secondly, a tree cutting decision-making model is established in combination with tree growth characteristics and ecological and economic benefits to obtain the expression of ecological and economic benefits and the carbon sequestration stock of trees under the optimal cutting cycle. By analyzing the operation of the management mode, it is found that the management mode is the acquisition of ecological forest system, and the combination of forest compensation and gradual cutting has the maximum benefit. Fitting can get that there is no case that no cutting is allowed. Finally, based on the existing data, the time series analysis is established to obtain the change curve of carbon sequestration and the change of forest area.


Carbon sequestration and oxygen release service model; Tree cutting decision-making model; Time series analysis

Cite This Paper

Hanlin Cui, Junye Jiang, Xue Ren. Research and Application of Carbon Storage Prediction and Management Evaluation Model. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 9: 14-21. https://doi.org/10.25236/AJCIS.2022.050903.


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