ForestAI: An AI-Powered Platform for Enhanced Forest Resource Assessment and Health Monitoring
April 5, 2025
In the southeastern United States, known as the wood basket of the nation, 70% of U.S. reforestation occurs, producing over 25% of the world's pulpwood and 18% of its saw timber, so advanced forest monitoring tools are increasingly critical in this region. To address this need, we developed ForestAI, a web-based platform leveraging artificial intelligence to enhance automated assessment, monitoring and projection of forest resources and health conditions.
Priorities, Pilots, and Goals
Current research priorities include validating the platform's effectiveness with existing data sources and real-world applications, particularly for early detection of pests and diseases. Future development will focus on integrating emerging technologies, high-resolution satellite imagery and structural measurements and advanced drone observations, to improve scalability. This research contributes to modernizing forest monitoring, data analytics, and decision-making support in the southeastern U.S., to enhance forest productivity and resilience while maintaining high standards of accuracy in resource assessment.
Species Distribution Model Workflow: Oak Wilt Disease Pilot Study
Our pilot study focuses on Oak Wilt disease detection and prediction, demonstrating the platform's capabilities for forest health monitoring.
Data Acquisition & Processing
- Climate Data Collection → Process Climate Variables
- Oak Wilt Data → Prepare Reference Dataset
- Split Training & Testing Data
Predictive Modeling
- XGBoost
- Random Forest
- SVM
- Neural Network
- Model Evaluation
Prediction & Validation
- Generate Oak Wilt Risk Predictions
- Generate Risk Maps and Reports
- Validate with Field Observations
