Forest Dataset

Forest datasets are crucial for advancing machine learning applications in forestry, encompassing diverse data modalities like LiDAR point clouds, aerial imagery, and thermal infrared images. Current research focuses on developing and benchmarking deep learning models for tasks such as tree species classification, individual tree segmentation, and forest scene understanding, often using synthetic data to augment limited real-world datasets. These datasets and associated algorithms are vital for improving forest management practices, enabling more accurate and efficient monitoring of forest health, biodiversity, and resource assessment.