Transmission Line Vegetation Hazard Prediction Image Dataset

With the global increase in energy demand, the safety and reliability of transmission networks have become particularly important. However, vegetation growth near transmission lines may lead to power interruptions, which is one of the challenges faced by the current industry. Existing manual inspection and monitoring methods are not able to meet the needs of large-scale applications due to high costs and low efficiency. This dataset aims to automatically detect and predict vegetation hazards around transmission lines through image recognition technology, improving inspection efficiency and accuracy. Data collection uses high-resolution drone cameras to capture transmission lines and their surrounding environment under various weather and lighting conditions. Quality control is ensured through multiple rounds of manual annotation, cross-validation, and review by forestry experts. The annotation team consists of professionals with experience in power and vegetation management, exceeding 50 people in size. Data preprocessing includes image correction, noise filtering, and image enhancement steps, stored in classified folders on a cloud platform.