• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.4
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• pp.356-368
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• 2021

To understand the temporal variation of phytoplankton communities in a coastal area, the biomass and diversity were weekly investigated in the inner bay of Yeong-do, Busan. In the study area, chlorophyll a concentration ranged from 0.43~7.58 mg m^-3 during the study, indicating the study area was in mesotrophic or eutrophic status. The fractions of chlorophyll a occupied by large phytoplankton (> 3 ㎛ diameter) exhibited an average of 80% of total chlorophyll a in this study. Among the large phytoplankton, while Bacillariophyta was the most dominant in spring and summer, Cryptophyceae prevailed in the fall and winter. On the contrary, in the picophytoplankton community less than 3 ㎛ in diameter, Mamiellophyceae was the most dominant in most seasons, Cryptophyceae was relatively high with an average of 17.7 ± 17.6% throughout the year, but seasonal variations were large. Dinophyceae rarely occupied a higher fraction up to 60.4% of the picophytoplankton community. By weekly monitoring at a coastal station for 13 months, it is suggested that phytoplankton communities in coastal waters could be changed on a short time scale. If data are steadily accumulated at the time-series monitoring site for a long time, these will provide important data for understanding the long-term dynamics of phytoplankton as well as the impact of climate and environmental changes.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Economic and Environmental Geology
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• v.55 no.1
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• pp.97-109
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• 2022

This study focused on the physicochemical effects of bottom ash dissolved precipitation on the soil and groundwater environment. The iced column and percolation experiments showed that most of the bottom ash particles were drained as the ash-dissolved solution, while the charcoal powder was filtered through the soil. Ion species of Al, As, Cu, Cd, Cr, Pb, Fe, Mn, Ca, K, Si, F, NO₃, SO₄ were analyzed from the eluates collected during the 24 h column test. In the charcoal powder eluates, a high concentration of K was detected at the beginning of the reaction, but it decreased with time. The concentrations of Al and Ca were observed to increase with time, although they existed in trace amount. In the bottom ash eluates, the concentrations of Ca and SO₄ decreased by 30 mg·L^-1 and 67 mg·L^-1, respectively, over 24 h. It is regarded that the infiltration patterns of the bottom ash and biochar in the unsaturated zone were different owing to their particle sizes and solvent properties. It is expected that a significant amount of the bottom ash will mix with the precipitation and percolate below the water table, especially in the case of thin and highly permeable unsaturated zone. The biochar was filtered through the unsaturated zone. The biochar did not dissolve in the groundwater, although it reached the saturation zone. For these reasons, it is considered that the direct contamination by the bottom ash and biochar are unlikely to occur.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.1
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• pp.101-119
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• 2022

Existing algal bloom monitoring is based on field sampling, and there is a limit to understanding the spatial distribution of algal blooms, such as the occurrence and spread of algae, due to local investigations. In this study, algal bloom monitoring was performed using an unmanned aerial vehicle and multispectral sensor, and data on the distribution of algae were provided. For the algal bloom monitoring site, data were acquired from the Mulgeum·Mae-ri site located in the lower part of the Nakdong River, which is the areas with frequent algal bloom. The Chlorophyll-a(Chl-a) value of field-collected samples and the Chl-a estimation formula derived from the correlation between the spectral indices were comparatively analyzed. As a result, among the spectral indices, Maximum Chlorophyll Index (MCI) showed the highest statistical significance(R²=0.91, RMSE=8.1mg/m³). As a result of mapping the distribution of algae by applying MCI to the image of August 05, 2021 with the highest Chl-a concentration, the river area was 1.7km², the Warning area among the indicators of the algal bloom warning system was 1.03km²(60.56%) and the Algal Bloom area occupied 0.67km²(39.43%). In addition, as a result of calculating the number of occurrence days in the area corresponding to the "Warning" in the images during the study period (July 01, 2021~November 01, 2021), the Chl-a concentration above the "Warning" level was observed in the entire river section from 12 to 19 times. The algal bloom monitoring method proposed in this study can supplement the limitations of the existing algal bloom warning system and can be used to provide information on a point-by-point basis as well as information on a spatial range of the algal bloom warning area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.334-345
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• 2022

The Enforcement Decree of the Framework Act on the Management of Disasters and Safety Article 3-2 specifies two 'disaster management supervision agencies' for responding to shipping disasters. These are the Korea Coast Guard, which is an on-scene disaster-responding and coordinating agency, and the Ministry of Ocean and Fisheries, which is a government department, thereby leading to possibilities for confusion. In the case of shipping disasters, where a personnel entitled full power to deal with shipping disasters is designated and his/her powers and duties are clearly made, relationship of leading and supporting agencies is made clear, and command system is simplified, an efficient response to shipping disasters is made possible. In the management of shipping disasters, all the disaster management processes, that is, prevention-preparedness-response-recovery, should be dealt with systematically and consistently. Notably, to swiftly and efficiently cope with a disastrous situation, the decision-making and command system must be simplified. The establishment of a command system and decision-making must be made independently, based on expertise. In the US, irrespective of the type of disasters, the FEMA plays a leading role and the USCG responds a response to maritime disasters by establishing the Incident Command System or Unified Command System that is an incident management system. In the UK, the MCA supervises an event and responds to it, and the SOSREP has full power to work with command and coordination independently. SOSREP, among others, is necessary to prevent an inefficient dealing of a shipping disaster owing to confrontation between participants. With reference to such leading States' practice, the Korean government should make a standardized and simplified response to maritime disasters. This study deals with a new maritime disaster responding system and provides an idea of the revision of the existing legal regime.

• Korean Journal of Heritage: History & Science
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• v.55 no.3
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• pp.46-58
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• 2022

This study analyzed the documentation trend of garden components such as plants, infrastructure, unit facilities, and structures, based on 188 measurement drawings of 94 old houses in a report on the documentation of the national folklore cultural heritage. The findings are as follows. First, it was found that plants and structures continuously appeared as the subject of measurement drawings, while infrastructure was often omitted. It was confirmed that unit facilities, which are smaller than other components, were frequently excluded from the documentation subject as well due to frequent changes such as movement, loss, and expansion. Second, the level of expression in measurement drawings showed different aspects for each component. The unit facilities showed a large change over time with respect to the level of documentation, and the level of documentation was somewhat polarized, particularly toward the latter stage. This suggests that the level of documenting the drawings limited to specific facilities improved, but the overall level of drawings did not improve, such as a lack of diversification of expression techniques suitable for various unit facilities. On the other hand, it was confirmed that the level of documenting the drawings for plants, infrastructure and structures did not change to a significant degree, implying that no improvements were made to the expression of components. Third, as for the technique of detailed expression, in the case of plants, vegetation status was prepared without distinction of old or protected trees that have historical value. Above all, there was no record of the vegetation structure that could help grasp the vegetation landscape of the outer area. As for the infrastructure, there was no consistent expression technique to systematically convey topographic changes such as the height and slope of the land. In addition, since there was no subtype classification defined for unit facilities and structures, there was no subject or method of documentation. This study is meaningful in that it expanded the category of documentation, which has been concentrated on buildings in old houses, to gardens, and called attention to the need for documenting the gardens for the preservation and management of old houses as an integration of the building and outer area.

• Journal of fish pathology
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• v.35 no.1
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• pp.1-25
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• 2022

The aquaculture industry has developed rapidly over the last three decades and is an important industry that supplies over 15% of humans' animal protein intake; therefore, there is a need to increase production to meet the continuous demand. The fish cage farms on the southern coast (Kyengsangnam-do and Jeollanam-do) of Korea are critical resources in aquaculture because they account for approximately 90% of the national total fish cage farms by water area ratio. However, the current aquaculture environment is being gradually affected by climate change, which is a global issue, and its effects are expected to intensify in the future. Therefore, it is urgently imperative to accurately evaluate the effects of climate change on South Korean aquaculture industries and to develop social and national strategies to minimize damage to the fishing industry. The damage to fish farmed in cage farms on the southern coast is increasing annually and the leading causes are high and low water temperature and red tides, which are directly or indirectly related to climate change. At present, global warming can provide opportunities for aquaculture industrialization of fish or other novel species, with economic implications. However, despite such opportunities, the influx of new species can also cause problems such as ecological disturbances, increase in the reproduction frequency of microalgae such as red tide, increase in disease incidence, and occurrence and periods of high water temperatures in summer. The scale of farmed fish mortality is increasing due to the complex effects of these factors. Increased damages due to fish mortality not only have severe economic impacts on the aquaculture industry, but the social costs of responding to the damage and follow-up measures also increase. various active responses can reduce the mortality damage in fish farms such as improving the management skills in aquaculture, improved species breeding, efficient food management, disease prevention, proactive responses, and system-wide improvements. This review article analyzes the large-scale mortality cases occurring in fish cage farms on the southern coast of Korea and proposes measures to mitigate mortality and enhance responses to such scenarios.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.