Institute of Forest Resource Information Techniques

Explainable XGBoost–SHAP Modeling Coupled with GeoDetector for Forest-Fire Occurrence Susceptibility and Future Climate Sensitivity in the Dabie Mountains

Forest-fire occurrence susceptibility prediction remains challenging in mountainous regions because fire occurrence is controlled by nonlinear interactions among climatic, vegetation, topographic, and anthropogenic factors. Developing interpretable prediction models that integrat...

The Development of Stand Growth Tables of Quercus mongolica Under Climate Change Scenarios

Numerous studies have demonstrated that climate exerts a substantial impact on forest growth. Traditional stand growth yield tables fail to take climatic factors into account, resulting in low accuracy and limited applicability. The study aimed to develop stand growth tables unde...