Study on average height prediction model of birch based on diameter at breast height information entropy

Zhuoqing Bai

doi:10.1117/12.2686318

28 July 2023 Study on average height prediction model of birch based on diameter at breast height information entropy

Zhuoqing Bai

Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127563I (2023) https://doi.org/10.1117/12.2686318
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

Predicting the average stature of trees is necessary to determine the biomass and carbon storage of a stand. The correlation between diameter at breast height and tree height has been extensively analysed and provides a reliable method to predict tree height. This study presents calculations of entropy information related to birch, the dominant tree species in a montane forest located in the northwestern region of Hebei Province. Six classical models (exponential, power, linear, logarithmic, Richard and logistic) are compared in this paper. Tests on the dataset showed that entropy data at breast diameter outperformed mean diameter in the ability to predict mean tree height. In addition, stratification of the data by breast diameter improved the accuracy of the model. This study proposes an optimisation method for predicting mean tree height by using entropy information at breast height and serves as a benchmark for comparable studies of multi-layered forests in the mountainous region of northwest Hebei Province, China. This paper examines and analyses the forest hierarchy based on a predictive model that analyses and predicts various factors of forest trees based on the underlying analytical model.

Citation Download Citation

Zhuoqing Bai "Study on average height prediction model of birch based on diameter at breast height information entropy", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127563I (28 July 2023); https://doi.org/10.1117/12.2686318

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KEYWORDS

Data modeling

Analytic models

Breast

Chest

Performance modeling

Statistical modeling

Climatology

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