Precision Forest Monitoring

Effective monitoring of forest resources is essential for the preservation and management of the environment. The technique for forest monitoring that employes drones equipped with LiDAR and RGB camera, along with advanced deep learning algorithms. The proposed methodology for precise tree counting and species identification by utilizing LiDAR data processing, image segmentation, and object techniques. LiDAR data processing uses RANSAC for canopy segmentation, while U-Net and YOLO algorithms are employed for tree detection and counting, respectively. Tree species identification involves feature extraction using ResNet and species classification with transfer learning using VGG- 16. This method shows better accuracy and efficiency than conventional methods, providing a comprehensive solution for management and biodiversity monitoring.