## 4 Conclusions  
Establishing a robust safety management system for LMO confined fields is paramount to avert the contamination of neighboring ecosystems. Particularly noteworthy is the integration of drones, which has revolutionized the production of vegetation maps, enabling nuanced monitoring of vegetation dynamics around LMO confined fields, surpassing the capabilities of conventional surveys. This study utilized a drone to capture high-resolution images and detailed information compared to satellite imagery. Another advantage of drone imagery is the segmented shooting intervals, enabling the prompt reflection of terrain changes around the LMO confined field and enhancing the mapping precision of  
Figure 6: Maps of vegetation distribution in the spring of 2022: relative dominance (**a**), importance value (**b**). Ai; _Artemisia indica_, **Aq**; _Akebia quinata_, **Cc**; _Conyza canadensis_, **Co**; _Commelina communis_, **Ea**; _Equisetum arreuse_, **Er**; _Erigeron annuus_, **La**; _Laminum amplexicaule_, **Ms**; _Miscanthus sacchariflorus_, **Ou**; _Oplismenus undulatifilius_, **To**; _Taraxacum officinalaule_, **Vs**; _Vicia sativa_, **Zj**; _Zoysia japonica_.  
the vegetation community. Furthermore, the aerial imagery process using drones helps to obtain comprehensive data, including areas previously inaccessible on target vegetation with enlarged survey coverage, swift investigation speed, and reduced workforce and expenses. This spatial data acquisition lays the groundwork for constructing a comprehensive database, a cornerstone for forging a sustainable, long-term approach to managing LMO leakage. This study's focal point centered on monitoring shifts within the safety management system, pinpointing the cultivation of LMOs within established confined fields, and encompassing pertinent species and corresponding flora. By orchestrating vegetation surveys in peripheral regions and harnessing drones for instantaneous topographical and spatial data collection, the potential for the newly suggested system was demonstrated. The developed monitoring system could be utilized safely and conveniently for the currently set up LMO confined fields in South Korea. Furthermore, it would evolve into a standard safety management system of the MOE's confined fields to be built in the future. In the forthcoming period, we intend to enhance the safety management framework for cultivating LMOs by employing drone technology to investigate plant clusters and leveraging artificial-intelligence-based deep learning techniques for the automated monitoring of vegetation alterations via image processing. In addition, we expect that the rapid and cumulative data acquisition could draw a preemptive strategy against the unintended release of LMOs into nature on vegetation monitoring, terrain change, etc. This will entail comparing drone-derived observations with actual vegetation survey results, fostering a deeper understanding of the system's practical implementation.  
Conceptualization, K.-H.N.; methodology, S.M.H. and K.-H.N.; investigation, S.M.H. and K.-H.N.; resources, S.M.H. and K.-H.N.; data curation, S.M.H., J.R.L. and K.-H.N.; writing--original draft preparation, S.M.H. and K.-H.N.; writing--review and editing, J.R.L. and K.-H.N.; supervision, J.R.L. and K.-H.N.; project administration, K.-H.N.; funding acquisition, J.R.L. and K.-H.N. All authors have read and agreed to the published version of the manuscript.  
This research was supported by a grant from the National Institute of Ecology (NIE), funded by the Ministry of Environment (MOE) of the Republic of Korea (NIE-A-2023-04).  
Not applicable.  
We would like to thank the many researchers and managers of the LMO Team, Invasive Alien Species Team, Natural Ecosystem Survey Team, Department of Landscape and Native Plants, and Department of Facility and Safety of the NIE for their help with the safe management of the LMO confined field.  
The authors declare no conflict of interest.