The agriculture sector is currently facing the problems of aging and decreasing skilled labor, meaning that the future direction of agriculture will be a transition to automation and mechanization that can maximize efficiency and decrease costs. Moreover, interest in the development of autonomous agricultural vehicles is increasing due to advances in sensor technology and information and communication technology (ICT). Therefore, an autonomous driving control algorithm using a low-cost global navigation satellite system (GNSS)-real-time kinematic (RTK) module and a low-cost motion sensor module was developed to commercialize an autonomous driving system for a crawler-type agricultural vehicle. Moreover, an autonomous driving control algorithm, including the GNSS-RTK/motion sensor integration algorithm and the path-tracking control algorithm, was proposed. Then, the performance of the proposed algorithm was evaluated based on three trajectories. The Root Mean Square Errors (RMSEs) of the path-following of each trajectory are calculated to be 9, 7, and 7 cm, respectively, and the maximum error is smaller than 30 cm. Thus, it is expected that the proposed algorithm could be used to conduct autonomous driving with about a 10 cm-level of accuracy.

In this study, simulation tests for gravity gradient referenced navigation (GGRN) are conducted to verify the effects of various factors such as database (DB) and sensor errors, flight altitude, DB resolution, initial errors, and measurement update rates on the navigation performance. Based on the simulation results, requirements for GGRN are established for position determination with certain target accuracies. It is found that DB and sensor errors and flight altitude have strong effects on the navigation performance. In particular, a DB and sensor with accuracies of 0.1 E and 0.01 E, respectively, are required to determine the position more accurately than or at a level similar to the navigation performance of terrain referenced navigation (TRN). In most cases, the horizontal position error of GGRN is less than 100 m. However, the navigation performance of GGRN is similar to or worse than that of a pure inertial navigation system when the DB and sensor errors are 3 E or 5 E each and the flight altitude is 3000 m. Considering that the accuracy of currently available gradiometers is about 3 E or 5 E, GGRN does not show much advantage over TRN at present. However, GGRN is expected to exhibit much better performance in the near future when accurate DBs and gravity gradiometer are available.

This analysis investigates the spatiotemporal variation of total cloud cover (TCC) across South Korea from 96 visual observation stations (VOS) during the years 2010–2019. The thin‐plate spline interpolation technique is used to interpolate the spatial variation of TCC within the country. The annual average of TCC distribution is closely related to topographical features and does not show excessive variation, with 50–56% over land. The seasonal TCC distribution has the lowest (highest) pattern in spring (summer), with a minimum (maximum) pattern of approximately 45% (95%). The lowest pattern in spring and highest pattern in summer may be due to the combined effect of lower cloud cover with TCC during March, and higher cloud cover with TCC from June to July. Interpolated VOS data are compared with the TCC obtained from ERA5 reanalysis products. The correlation coefficient between VOS and ERA5 is higher than 0.80 on the eastern coast, and approximately 0.20–0.40 on the western coast, indicating a strong and poor sampling effect. The largest variability between VOS and ERA5 is observed during the winter season, with a percentage deviation of −70–20%, possibly due to inaccurate cloud detection under cold low‐level atmospheric temperatures or snow cover. In summer, variability is −35–40%, which is slightly less than that in winter, possibly because of the incorrect detection of frequently occurring cumulus clouds. Principal component analysis of the TCC variability used to examine the relationship with other climate parameters. The first principal component, containing the major portion, correlated with precipitation, diurnal temperature, humidity, atmospheric pressure, and wind speed, with correlation coefficients of 0.293, 0.246, −0.360, −0.258, and 0.470, respectively, indicating positive or negative relationship. We believe the outcomes from this study will contribute a better understanding of climate over South Korea and establish links between East Asia and the Pacific Ocean cloud formation.

The global navigation satellite system (GNSS)-derived height determination technique is applied in the field of surveying owing to the broad use of GNSS and the development of precise local geoid models. In Korea, this technique was officially adopted in 2020 for public surveying, such as urban facility mapping; it is also treated as an efficient way to unify the vertical datum of the inland and island areas of Korea. Here, GNSS surveying was conducted on 19 stations located in Korea’s coastal regions and islands, and GNSS-derived elevations were determined. When each GNSS-derived elevation was compared with elevations from spirit leveling, all stations showed differences of less than 3 cm when GNSS surveying was conducted for 4 h/day over two days; they were smaller than 5 cm with 2 h of surveying. These differences meet the standards of GNSS-derived elevations in Korea. In addition, GNSS-derived elevations were compared with those obtained via sea-crossing leveling in two regions, showing differences smaller than 1 cm. Sea-crossing leveling takes longer than GNSS-derived height determination, and its accuracy can be significantly affected by various environments, such as sea fog. Thus, GNSS-derived height determination represents a practical and useful technique.

Jeong, S.-H.; Kwon, J.H., and Lee, J., 2023. Analysis of rip current flow fields in CCTV images using optimal LSPIV parameters. In: Lee, J.L.; Lee, H.; Min, B.I.; Chang, J.-I.; Cho, G.T.; Yoon, J.-S., and Lee, J. (eds.), Multidisciplinary Approaches to Coastal and Marine Management. Journal of Coastal Research, Special Issue No. 116, pp. 240-244. Charlotte (North Carolina), ISSN 0749-0208. Research on rip currents can be conducted through indoor studies with numerical simulation tests or by studies that analyze data by installing instruments in the actual ocean. For flow field studies using measuring instruments, data are collected by installing an Acoustic Wave Current Measurement (AWAC) or Acoustic Doppler Current Profiler (ADCP). It is not appropriate in terms of effectiveness, cost, and accuracy to analyze data obtained in a specific area by applying it to the entire flow field. In this study, the applicability and limitations of the Large Scale Particle Image Velocimetry (LSPIV) technique were derived for Closed-circuit Television (CCTV) images of rip currents in Haeundae by applying the optimal velocity calculation parameters. For LSPIV analysis, the tilted CCTV image was tilt-corrected using 208 GCPs and Affine Transformation and stabilized using feature points. The flow rate calculated with 18 parameters by combining 6 interrogation areas and 3 searching areas was compared with the average flow rate of the normal distribution confidence interval. As the size of the parameter changes, the error rate changes along with its characteristics. Compared to the average flow rate, three parameters with errors within 2% were determined as LSPIV flow rate calculation parameters. The flow velocities calculated with the determined parameters were 0.196 m/sec, 0.205 m/sec, and 0.207 m/sec within a maximum range of 5.31%. In addition, it was found that the flow velocity increased, and the error decreased as the size of the interrogation area increased. The LSPIV velocity vector overlapped with the rip current's foam image in the tilt-corrected CCTV image to confirm the degree of matching. In the future, if several high-resolution CCTVs are used and stereo image-based object detection and 3D location tracking algorithms are applied to the analysis area, it can be a good alternative as a direct measurement analysis verification method of marine data.