Yeongjae Jang

Unvegetated tidal flats store sedimentary organic carbon (OC), but their contribution to blue-carbon inventories remains poorly constrained because sparse cores must represent heterogeneous intertidal environments. This study quantified OC stock within the upper 1 m of Hwangdo tidal flat, South Korea, by integrating ten 100-cm cores, 107 surface-sediment samples, and an unmanned-aerial-vehicle-derived digital elevation model covering 4.841 km². The surface survey characterized variations in elevation, sediment texture, and OC, while the cores provided profiles of grain size, dry bulk density, and OC content. Core stocks were integrated over 0–100 cm and evaluated using a spatially grouped, cross-validated adjustment based on surface elevation and uppermost-sediment OC to reduce bias from sparse core distribution. Measured core stocks ranged from 13.61 to 30.20 Mg C ha⁻¹, with an unadjusted mean of 23.04 Mg C ha⁻¹. Mean OC contents were low in surface sediments (0.18%) and core sediments (0.17%). Across the pooled surface and core dataset, TOC correlated positively with mud content (Spearman’s ρ = 0.47) and negatively with sand content (ρ = −0.51), indicating sediment-textural control over OC distribution. The adjustment increased the mean stock by 5.9% to 24.39 Mg C ha⁻¹. Applying this value to 484.108 ha yielded a regional OC storage of 11.81 Gg C, with a conditional bootstrap interval of 9.12–12.90 Gg C. However, the low cross-validated Q² (0.070) shows that the model adjusts the core mean rather than providing a spatially explicit prediction. Overall, Hwangdo’s comparatively low OC pool likely reflects the combined effects of limited inputs of terrestrial organic matter; the absence of vascular vegetation and the associated belowground biomass that would otherwise promote carbon retention; and the frequent reworking, oxygenation, and export of organic matter from its sand-dominated, hydrodynamically energetic sediments. By integrating depth-resolved cores with dense surface observations and UAV-derived topography while explicitly reporting conditional uncertainty, this study establishes a transferable framework for more defensible blue-carbon inventories and strategically targeted sampling in data-limited unvegetated tidal flats.

Understanding suspended sediment transport in macrotidal embayments is crucial for assessing water quality, ecosystem function, and long-term morphological stability. This study provides a high-resolution, localized estimate of suspended sediment flux and examines the empirical relationship between turbidity (NTU, nephelometric turbidity unit) and total suspended matter (TSM, mg·L⁻¹) in the main tidal channel of Gomso Bay, a UNESCO-designated tidal flat on the west coast of Korea. A 13 h high-resolution fixed-point observation was conducted during a semi-diurnal tidal cycle using a multi-instrument platform, including an RCM, CTD profiler, tide gauge, and water sampling for gravimetric TSM analysis. Vertical measurements at the surface, mid, and bottom layers, taken every 15–30 min, revealed a strong linear correlation (R² = 0.94) between turbidity and TSM, empirically validating the use of optical sensors for real-time sediment monitoring under the highly dynamic conditions of Korean west-coast tidal channels. The net suspended sediment transport load was estimated at approximately 5503 kg·m⁻¹, with ebb-dominant residual currents indicating a net seaward sediment flux at the observation site. Residual flows over macrotidal channels are known to vary laterally, with landward fluxes often occurring over shoals. Importantly, the results from this single-station, short-duration observation indicate a predominantly seaward suspended sediment transport during the study period, which should be interpreted as a localized and time-specific estimate rather than a bay-wide characteristic. Nevertheless, these findings provide a baseline for assessing sediment flux and contribute to future applications in digital twin modeling and coastal management. Gomso Bay is part of the UNESCO-designated ‘Getbol, Korean Tidal Flats’, underscoring the global significance of preserving and monitoring this dynamic coastal system.

The importance of blue carbon is significant in terms of climate change mitigation and marine ecosystem conservation, and halophyte acts as a crucial reservoir for this blue carbon. Accordingly, this study utilized unmanned aerial vehicle (UAV) optical sensors to create a distribution map of vegetation in the natural salt marsh of the Jujin estuary. The optical images captured from a UAV at an altitude of 50 m provide ultra-high-resolution optical information with a ground sampling distance of 0.6 cm. Based on these images, a U-Net model was trained to classify Phragmites communis and Suaeda maritima, generating a classification map of the mixed habitats of salt marsh plants. The areas of Phragmites communis and Suaeda maritima in the Jujin- Cheon region were found to be 6,653.23 m2 and 1,409.08 m2, respectively. The classification results were validated using field control point data, confirming an approximate classification accuracy of 92%.

This study analyzes the geological and geochemical features of surface sediments in the Hwangdo Tidal Flat, located on Korea’s West Coast. The tidal flat experiences semi-diurnal tides, impacting organic matter decomposition and nutrient cycling. Ninety one sediment samples were collected and analyzed for physical and chemical properties including grain size, density, water content, organic carbon, and nitrogen. Sediments consist mainly of sand and silt, with coarser sediments near the main channel and finer sediments towards the west. Sediment grain size averages 4.12 Φ with a sorting coefficient of 1.96 Φ, indicating diverse energy environments. Total organic carbon and nitrogen correlate positively with grain size and density, reflecting sediment origin and environment. Kriging maps sediment grain size distribution, while correlation and linear regression analyses show relationships between variables. High correlations exist between various parameters, aligning with tidal flat characteristics and aiding understanding of sediment transport and deposition. The study provides baseline data for understanding the tidal flat’s geological, geochemical, and physical aspects, valuable for remote sensing validation and environmental monitoring. The dataset is freely available for research and management purposes.

Intertidal macroinvertebrates, such as crabs and mud shrimps, are invertebrates inhabiting the intertidal zone that are sufficiently large to be identified with the naked eye. Most intertidal macroinvertebrates typically construct burrows of various shapes in sediment to protect themselves from environmental extremes, with surface openings that reflect features of their species and body size. Especially circular burrow openings correlate with an organism’s body size; thus, measuring these openings can provide estimates of the organism’s size, weight, growth rate, and biomass. Traditional studies of these organisms have relied on field surveys, which are constrained by time, cost, and logistical limitations. This study introduces an innovative method for measuring the burrow opening diameters of intertidal macroinvertebrates using high-resolution optical images from a portable drone system. By leveraging the reflectance disparity between the sediment and burrow openings, this method facilitates the extraction and sizing of burrow openings. Our methodology was applied to three crab species known for their circular burrow opening: the red-clawed fiddler, the milky fiddler, and the ghost crab. Validation was confirmed through field data from the Mageumri and Sinduri tidal flats, South Korea. The method achieved a correlation coefficient (R²) of 0.94 and a root mean squared error (RMSE) of 1.68 mm across a diameter range of 6.21–33.59 mm. These findings suggest the potential of drone remote sensing systems as a non-invasive and efficacious approach for quantifying burrow sizes over extensive intertidal areas, thereby facilitating more accurate biomass estimations and surmounting the limitations of conventional field surveys. Future research could extend this method to additional species and further refine its precision.

The Hwangdo tidal flat is an intertidal landform located in Cheonsu Bay, Taean-gun, Chungcheongnam-do, on the west coast of Korea. The topographical characteristics of the semi-enclosed bay on the eastern side of the study area include waterways, sandbars, small islands, and tidal flats. In this study, data were acquired from tide gauges installed on the Hwangdo Bridge, and the height of the ellipsoid was measured using a real-time kinematics global positioning system (RTK-GPS). Digital elevation model (DEM) using Matrice 300 drone data were also acquired after processing. The geochemical sediment characteristics in the study area were analyzed, together with tidal-flat exposure-time characteristics based on environmental factors. Sediment data (n = 107) collected from October 25 to 28, 2022 (Korean local time) were used to classify sediment particles according to Folk and Ward (1957). Sedimentary facies ranged from coarse sand (sand:mud ratio = 9:1) to sandy silt (sZ) followed by muddy sand (mS) and slightly gravelly sandy mud ((g)sM). Total organic carbon (TOC) in the surface sediments was also characterized based on a particle-size analysis. The mean change in tidal height measured at Hwangdo Bridge during the sampling period was ~7.53 m (minimum: −3.86 m, maximum: +3.67 m). Based on the Boryeong’s sea level measurement tide data in 2022, the tidal area in the drone images ranged from 6.362 m² (0.006 km²) at DEM +4.0 to 4,841,078 m² (4.841 km²) at DEM −4.0 m, indicating an increase in the tidal-flat area according to the tidal level of up to ~800-fold. The daily average exposure time was 9.0 h (minimum: 1.5 h, maximum: 17.9 h). Based on the results of multivariate analysis using exposure times and a geochemical dataset, four groups were identified: upper, middle, and lower intertidal zones and regions with a relatively high organic-matter concentration. A determination of the main characteristics of the Hwangdo tidal flat according to their spatial distribution showed that, among various environmental factors, changes in the sand or clay sediment composition were determined by community factors. The results of this study demonstrate the four statistically processed groups of marine environmental characteristics in the Hwangdo tidal flats. Changes in sedimentary patterns, rather than in the exposure time, accounted for the differences in the sediment compositions of the upper, middle, and lower stations, a response that is expected to continue.

The Hwangdo tidal flat is an intertidal landform located in Cheonsu Bay, Taean-gun, Chungcheongnam-do, on the west coast of Korea. The topographical characteristics of the semi-enclosed bay on the eastern side of the study area include waterways, sandbars, small islands, and tidal flats. In this study, data were acquired from tide gauges installed on the Hwangdo Bridge, and the height of the ellipsoid was measured using a real-time kinematics global positioning system (RTK-GPS). Digital elevation model (DEM) using Matrice 300 drone data were also acquired after processing. The geochemical sediment characteristics in the study area were analyzed, together with tidal-flat exposure-time characteristics based on environmental factors. Sediment data (n = 107) collected from October 25 to 28, 2022 (Korean local time) were used to classify sediment particles according to Folk and Ward (1957). Sedimentary facies ranged from coarse sand (sand:mud ratio = 9:1) to sandy silt (sZ) followed by muddy sand (mS) and slightly gravelly sandy mud ((g)sM). Total organic carbon (TOC) in the surface sediments were also characterized based on a particle-size analysis. The mean change in tidal height measured at Hwangdo Bridge during the sampling period was ~7.53 m (minimum: –3.86 m, maximum: +3.67 m). Based on the Boryeong's sea level measurement tide data in 2022, the tidal area in the drone images ranged from 6.362 m² (0.006 km²) at DEM +4.0 to 4,841,078 m² (4.841 km²) at DEM –4.0 m, indicating an increase in the tidal-flat area according to the tidal level of up to ~800-fold. The daily average exposure time was 9.0 h (minimum: 1.5 h, maximum: 17.9 h). Based on the results of multivariate analysis using exposure times and a geochemical dataset, four groups were identified: upper, middle, and lower intertidal zones and regions with a relatively high organic-matter concentration. A determination of the main characteristics of the Hwangdo tidal flat according to their spatial distribution showed that, among various environmental factors, changes in the sand or clay sediment composition were determined by community factors. The results of this study demonstrate the four statistically processed groups of marine environmental characteristics in the Hwangdo tidal flats. Changes in sedimentary patterns, rather than in the exposure time, accounted for the differences in the sediment compositions of the upper, middle, and lower stations, a response that is expected to continue.

Recent advances in deep learning (DL) and unmanned aerial vehicle (UAV) technologies have made it possible to monitor salt marshes more efficiently and precisely. However, studies have rarely compared the classification performance of DL with the pixel-based method for coastal wetland monitoring using UAV data. In particular, many studies have been conducted at the landscape level; however, little is known about the performance of species discrimination in very small patches and in mixed vegetation. We constructed a dataset based on UAV-RGB data and compared the performance of pixel-based and DL methods for five scenarios (combinations of annotation type and patch size) in the classification of salt marsh vegetation. Maximum likelihood, a pixel-based classification method, showed the lowest overall accuracy of 73%, whereas the U-Net classification method achieved over 90% accuracy in all classification scenarios. As expected, in a comparison of pixel-based and DL methods, the DL approach achieved the most accurate classification results. Unexpectedly, there was no significant difference in overall accuracy between the two annotation types and labeling data sizes in this study. However, when comparing the classification results in detail, we confirmed that polygon-type annotation was more effective for mixed-vegetation classification than the bounding-box type. Moreover, the smaller size of labeling data was more effective for detecting small vegetation patches. Our results suggest that a combination of UAV-RGB data and DL can facilitate the accurate mapping of coastal salt marsh vegetation at the local scale.