• Journal of Korean Society of Rural Planning
• /
• v.30 no.1
• /
• pp.57-66
• /
• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Korean Journal of Environment and Ecology
• /
• v.30 no.6
• /
• pp.1022-1031
• /
• 2016

Relationships of standing biomass with biodiversity and structural diversity were examined in the Quercus mongolica-dominated forest in Mt. Jeombong, Gangwon-do. We examined the standing biomass of the Q. mongolia community ($311.1ton{\cdot}ha^{-1}$) from 2004 to 2013, and the observed major species were Q. mongoilca, Carpinus cordata, Tilia amurensis whose standing biomasses were $206.3ton{\cdot}ha^{-1}$ (66.3%), $36.9ton{\cdot}ha^{-1}$ (11.9%), and $30.6ton{\cdot}ha^{-1}$ (9.8%), respectively. Although the number of Q. mongolica individuals was very small compared with total density, the reason that Q. mongolica showed the most biomass than other species is due to greater average diameter at breast height (DBH) and the higher number of $DBH{\geq}50cm$ individuals. We calculated the range of Shannon index (H') and Shannon evenness (J') in the Q. mongolica community, and they were gradually increased in time, showing 2.015~2.166, 0.673~0.736, respectively. Their H' and J' showed positive linear relationships with their standing biomass. This indicates that the spatial distribution of the standing biomass in Q. mongoilca community becomes more homogeneous with time and this homogenization appears in various species in the community. In addition, we estimated biomass-species index (BS) and abundance-biomass-speciesdiversity (ABS) and they also showed gradual increase in time, ranging from 3.746 to 3.811 and from 4.781 to 5.028, respectively. Their indices showed positive linear relationships with the standing biomass. This can be explained from the observations of variations in standing biomass with tree diameters as the differences in the average standing biomass in the community have reduced gradually in time. Moreover, it is expected that increase in the structure diversity of the Q. mongoilca community enhances the efficiency in carbon sequestration and productivity, so the community can be developed to a more sustainable ecosystem with more abundant resources. Thus, applications of uneven-aged plantations with considerations of local ecological properties can be a very efficient reforestation method to ensure stable support of biodiversity and productivity.

• Journal of the Korean Crystal Growth and Crystal Technology
• /
• v.34 no.4
• /
• pp.109-116
• /
• 2024

β-Ga₂O₃ is a representative ultra-wide bandgap (UWBG) semiconductor that has attracted much attention for power device applications due to its wide-bandgap of 4.9 eV and high-breakdown voltage of 8 MV/cm. In addition, because solution growth is possible, it has advantages such as fast growth rate and lower production cost compared to SiC and GaN [1-2]. In this study, we have successfully grown Si-doped 10 mm thick Si-doped β-Ga₂O₃ single crystals by the EFG (Edge-defined Film-fed Growth) method. The growth direction and growth principal plane were set to [010] / (010), respectively, and the growth speed was 7~20 mm/h. The as-grown β-Ga₂O₃ single crystal was cut into various crystal planes (001, 100, ${\bar{2}}01$) and off-angles (1^o, 3^o, 4^o), and then surface processed. After processed, the homoepitaxial layer was grown on the epi-ready substrate using the HVPE (Halide vapor phase epitaxy) method. The processed samples and the epi-layer grown samples were analyzed by XRD, AFM, OM, and Etching to compare the surface properties according to the crystal plane and off-angle.