## 3 Results and Discussion
### Elevating Vegetation Monitoring with Drones: Real-Time Insights and Species Dominance Mapping  
Vegetation maps conventionally relied on satellite map services or aerial images furnished by the National Geographic Information Institute. However, these approaches could not capture real-time vegetation changes. In contrast, drones offer a holistic view of actual vegetation shifts through their real-time, high-resolution image capture. Drones unveiled the evolution of buildings around the LMO confined field and topographical transformations due to precipitation and seasonal vegetation variations. In conclusion, using drones to capture high-resolution aerial images represents a valuable technique to monitor vegetation changes [12; 35]. In our study, drones provided real-time images that allowed for a comprehensive view of the actual vegetation dynamics, including the construction process of buildings, topographical changes due to rainfall, and seasonal variations in vegetation. The use of drones holds promise for various applications, including land development, forest management, and plant sociological spatial analysis [36]. Furthermore, [PERSON] et al. [37] reported that drones have the capability to discern invasive plant species in arid regions that are susceptible to wildfires and floods. In May 2022, vegetation shifts were recorded via drone images, culminating in creating of a vegetation map (Figure 6). The map elucidates variations in vegetation coverage by pinpointing dominant species within observed areas. It leverages the relative dominance of vegetation cover to discern primary species in the monitored regions. Notably, _Convza canadensis_ reigned supreme as the dominant species within the LMO confined field, while graminoid plants such as _Oplismens undulatifolius_ dominated the 25 m forest area. Shrubbery predominated the 50- and 100 m zones, with _Akebia quinata_ claiming dominance. Non-forest domains saw a shift in dominant species, with _Taraxacum officinal_ taking the lead in the 25 m region, _Zoysia japonica_ encircling buildings, and _Miscanthus sacchariforus_ lin  
Figure 5: Results of orthomosaic imaging (**a**), digital elevation model (DEM) (**b**), precise polygon (**c**), and vegetation map (**d**). ing waterways at 50 m. In the 100 m expanse, _Zoysia japonica_, meticulously managed due to its proximity to structures, emerged as the predominant species, whereas _Vicia sativa_ dominated the unattended areas. The vegetation importance value was harnessed to construct the vegetation map, spotlighting _Conyza canadensis_ as the most significant species within the LMO confined field. _Laminum amplexicaule_ held sway in the 25 m forest region, while _Equisetum arreuse_ commanded dominance at 50 and 100 m. _Taraxacum officinalaule_ claimed the highest importance value in non-forest zones at 25 m, while _Zoysia japonica_ secured the spotlight at 50 and 100 m. The outcomes unveiled that alterations in vegetation were steered by distance and human activity. Nevertheless, variations in dominant species were intricately linked to topography in the unmanaged sectors. These revelations underscore the essentiality of meticulous observation concerning shifts in unattended forest areas, especially following the release of LMOs into the ecosystem. Detecting LMOs can be formidable, fraught with diverse ecological risks [3]. In contrast, to comprehend the impact of LMO leakage on the ecosystem surrounding the confined field, it is imperative to accumulate spatial change data on a seasonal and yearly basis. In addition to the data obtained through temporary drone surveys, it is essential to conduct continuous data accumulation over time to analyze the surrounding changes, analogous to vegetation surveys [38]. Our findings specifically demonstrated the potential of using a Geographic Information System (GIS) database to establish, analyze, and manage comprehensive spatial and vegetation information derived from drone imagery, thereby enabling effective safety management of LMO confined fields.