Integrating ensemble learning and rocky desertification indices improves accuracy and interpretability of soil thickness prediction in karst landscapes

Key Points

• Soil thickness prediction accuracy improved through integration of innovative techniques, enhancing data utility and environmental analysis.
• Using ensemble learning and rocky desertification indices, predictions achieved up to a 20% increase in accuracy compared to traditional methods.
• This approach employed predictive modeling to analyze soil characteristics across diverse karst landscape regions effectively.
• Findings support the need for improved interpretability in environmental assessments, suggesting better land management outcomes.