LIDAR Dataset Validation for Enhancing Vegetation Management in Distribution System Operator Powerline Infrastructure
2024 IEEE 65th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2024): Proceedings
2024
Diāna Gauče,
Anna Litviņenko
This study investigates the use of LIDAR technology to enhance vegetation management practices for powerline infrastructure within a Distribution System Operator (DSO) framework. The research focuses on validating LIDAR datasets for identifying vegetation encroachment and assessing its impact on powerline safety and maintenance. The experimental process included data acquisition, processing, and risk assessment based on vegetation volumes to powerlines. Results from the LIDAR analysis were compared to traditional manual inspections, revealing a high level of accuracy, with discrepancies primarily attributable to human error, within a 10% margin. The findings demonstrate the potential for automating vegetation monitoring, improving decision-making, and reducing the time and resources required for fieldwork. This approach paves the way for future innovations in predictive vegetation management and risk mitigation strategies using geospatial data.
Keywords
LIDAR, vegetation management, data analysis, geospatial analysis, data-driven decision-making, automation, Distribution System Operator, powerline infrastructure, overhead lines, infrastructure safety
DOI
10.1109/ITMS64072.2024.10741947
Hyperlink
https://ieeexplore.ieee.org/abstract/document/10741947
Gauče, D., Litviņenko, A. LIDAR Dataset Validation for Enhancing Vegetation Management in Distribution System Operator Powerline Infrastructure. In: 2024 IEEE 65th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2024): Proceedings, Latvia, Riga, 3-4 October, 2024. Piscataway: IEEE, 2024, pp.134-138. ISBN 979-8-3315-3384-7. e-ISBN 979-8-3315-3383-0. ISSN 2771-6953. e-ISSN 2771-6937. Available from: doi:10.1109/ITMS64072.2024.10741947
Publication language
English (en)