Integration and Application of Big Data Technology in Forest Growth Prediction and Effect Evaluation
Abstract：The application of big data analysis technology in the field of forestry engineering, especially in forest growth prediction, shows great potential. It integrates multi-dimensional data such as climate, soil, and water to make accurate predictions of forest growth, and evaluates the prediction effects by combining actual growth data. The results show that big data technology can effectively improve the prediction accuracy of forest growth models, reduce uncertainties in traditional methods, and provide a scientific basis for forestry management. This paper discusses the application value of big data in forest growth prediction from multiple aspects, including data collection, model construction, and evaluation of prediction effects, and proposes further optimization directions.
Keywords：Big Data AnalysisForestry EngineeringEffect EvaluationModel Construction
Publication Date：2025-02-27
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 47-49,78 )