• Korean Journal of Ecology and Environment
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• v.48 no.1
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• pp.61-67
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• 2015

This study, which was conducted from Apr. 2013 to Jan. 2014, was carried out as part of a project of making a more detailed ecological zoning map with 1/5,000 scale. The necessity of electronic vegetation map with large scale has arisen in order to make the best use of basic research findings on resource monitoring of National Parks and to enhance efficiency in National Park management. In order to improve accuracy and speed of vegetation research process, the data base for vegetation research was categorized into five groups, namely broad-leaved forest, coniferous forest, mixed forest, rock vegetation and miscellaneous one. And then a vegetation map for vegetation research was created for the research on the site. What is in the database for vegetation research and the vegetation map reflecting findings from vegetation research showed similar distribution rate for broad-leaved forest with 71.965% and 71.184%, respectively. The distribution rate of coniferous forest (16.010%, 15.747%), mixed forest (10.619%, 12.085%), and rock vegetation (0.015%, 0.002%) did not have much difference. In a detailed vegetation map reflecting vegetation research findings, the broad-leaved mountain forest was the most widely distributed with 60.096% based on the physiognomy classification. It was followed by mountain coniferous forest (16.332%), mountain valley forest (15.887%), and plantation forest (3.558%) As for vegetation conservation classification evaluated in the national park, grade I and grade II areas took up 200.44 km2, 61.80% and 108.80 km2, 33.55% respectively. The combined area of these two amounts to 95.35%, making this area the first grade area in ecological nature status. This means that this area is highly worth preserving its vegetation. The high rate of grade I area such as climax forests, unique vegetation, and subalpine vegetation seems to be attributable to diverse innate characteristics of Odaesan National Park, high altitude, low level of artificial disturbance, the subalpine zone formed on the ridge of the mountain top, and their vegetation formation, which reflects climatic and geological characteristics, despite continuous disturbance by mountain climbing.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.237-237
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• 2015

The district of Marlborough has had more than its share of river management projects over the past 150 years, each one uniquely affecting the geomorphology and flood hazard of the Wairau Plains. A major early project was to block the Opawa distributary channel at Conders Bend. The Opawa distributary channel took a third and more of Wairau River floodwaters and was a major increasing threat to Blenheim. The blocking of the Opawa required the Wairau and Lower Wairau rivers to carry greater flood flows more often. Consequently the Lower Wairau River was breaking out of its stopbanks approximately every seven years. The idea of diverting flood waters at Tuamarina by providing a direct diversion to the sea through the beach ridges was conceptualised back around the 1920s however, limits on resources and machinery meant the mission of excavating this diversion didn't become feasible until the 1960s. In 1964 a 10 m wide pilot channel was cut from the sea to Tuamarina with an initial capacity of $700m^3/s$. It was expected that floods would eventually scour this 'Wairau Diversion' to its design channel width of 150 m. This did take many more years than initially thought but after approximately 50 years with a little mechanical assistance the Wairau Diversion reached an adequate capacity. Using the power of the river to erode the channel out to its design width and depth was a brilliant idea that saved many thousands of dollars in construction costs and it is somewhat ironic that it is that very same concept that is now being used to deal with the aggradation problem that the Wairau Diversion has caused. The introduction of the Wairau Diversion did provide some flood relief to the lower reaches of the river but unfortunately as the Diversion channel was eroding and enlarging the Lower Wairau River was aggrading and reducing in capacity due to its inability to pass its sediment load with reduced flood flows. It is estimated that approximately $2,000,000m^3$ of sediment was deposited on the bed of the Lower Wairau River in the time between the Diversion's introduction in 1964 and 2010, raising the Lower Wairau's bed upwards of 1.5m in some locations. A numerical morphological model (MIKE-11 ST) was used to assess a number of options which led to the decision and resource consent to construct an erodible (fuse plug) bank at the head of the Wairau Diversion to divert more frequent scouring-flows ($+400m^3/s$)down the Lower Wairau River. Full control gates were ruled out on the grounds of expense. The initial construction of the erodible bank followed in late 2009 with the bank's level at the fuse location set to overtop and begin washing out at a combined Wairau flow of $1,400m^3/s$ which avoids berm flooding in the Lower Wairau. In the three years since the erodible bank was first constructed the Wairau River has sustained 14 events with recorded flows at Tuamarina above $1,000m^3/s$ and three of events in excess of $2,500m^3/s$. These freshes and floods have resulted in washout and rebuild of the erodible bank eight times with a combined rebuild expenditure of $80,000. Marlborough District Council's Rivers & Drainage Department maintains a regular monitoring program for the bed of the Lower Wairau River, which consists of recurrently surveying a series of standard cross sections and estimating the mean bed level (MBL) at each section as well as an overall MBL change over time. A survey was carried out just prior to the installation of the erodible bank and another survey was carried out earlier this year. The results from this latest survey show for the first time since construction of the Wairau Diversion the Lower Wairau River is enlarging. It is estimated that the entire bed of the Lower Wairau has eroded down by an overall average of 60 mm since the introduction of the erodible bank which equates to a total volume of $260,000m^3$. At a cost of $$0.30/m^3$ this represents excellent value compared to mechanical dredging which would likely be in excess of $$10/m^3$. This confirms that the idea of using the river to enlarge the channel is again working for the Wairau River system and that in time nature's "excavator" will provide a channel capacity that will continue to meet design requirements.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1657-1667
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• 2021

Anthropogenic activities and natural processes have been causes of land subsidence which is sudden sinking or gradual settlement of the earth's solid surface. Mexico City, the capital of Mexico, is one of the most severe land subsidence areas which are resulted from excessive groundwater extraction. Because groundwater is the primary water resource occupies almost 70% of total water usage in the city. Traditional terrestrial observations like the Global Navigation Satellite System (GNSS) or leveling survey have been preferred to measure land subsidence accurately. Although the GNSS observations have highly accurate information of the surfaces' displacement with a very high temporal resolution, it has often been limited due to its sparse spatial resolution and highly time-consuming and high cost. However, space-based synthetic aperture radar (SAR) interferometry has been widely used as a powerful tool to monitor surfaces' displacement with high spatial resolution and high accuracy from mm to cm-scale, regardless of day-or-night and weather conditions. In this paper, advanced interferometric approaches have been applied to get a time-series of land subsidence of Mexico City using four-year-long twenty ALOS PALSAR L-band observations acquired from Feb-11, 2007 to Feb-22, 2011. We utilized persistent scatterer interferometry (PSI) and small baseline subset (SBAS) techniques to suppress atmospheric artifacts and topography errors. The results show that the maximum subsidence rates of the PSI and SBAS method were -29.5 cm/year and -27.0 cm/year, respectively. In addition, we discuss the different subsidence rates where the study area is discriminated into three districts according to distinctive geotechnical characteristics. The significant subsidence rate occurred in the lacustrine sediments with higher compressibility than harder bedrock.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.224-255
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• 2022

This study was carried out to examine the changes in vascular flora in the first and second surveys targeting 32 outstanding forest wetlands in Jeonnam area including Gwangju metropolitan city, and based on this, establish a future monitoring system and effectively manage the excellent forest wetlands. The survey investigated the area seasonally every 4-5 years from 2015 to 2021. The change of flora of 32 excellent forest wetlands in Jeollanam-do increased from 103 families, 311 genera, 496 species, 16 subspecies, 38 varieties, 6 varieties, 556 taxa, to 111 families, 362 genera, 599 species, 16 subspecies, 51 varieties, 8 varieties, 674 taxa. Remarkable plants such as Red list and plants endemic to the Korean Peninsula increased also. However, Nepeta cataria and the like are exterminated locally, so an in situ and ex situ conservation strategy must be established. In the case of plants categorized according to wetland preference, the distribution ratio of such wetland plants slightly decreased and the distribution ratio of such terrestrial plants lightly increased for absolute wetland plants. It is necessary to prepare countermeasures for the terrestrialization of forest wetlands and to develop research techniques that can distinguish boundaries. In addition, the forest wetland should be systematically managed and supervised by designating it as a Forest Genetic Resources Reserve that can effectively conserve it.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.100-107
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• 2021

Along with an increase in the frequency of high-concentration fine particulate matter in Korea, interest and research on ammonia (NH₃) are actively increasing. It is obvious that agriculture has contributed significantly to NH₃ emissions. However, studies on the long-term effect of fertilizer use on the ambient NH₃ concentration of agricultural land are insufficient. Therefore, in this study, NH₃ concentration in the atmosphere of agricultural land was monitored for 11 months using a passive sampler. The average ambient NH₃ concentration during the total study period was 2.02 ㎍ m^-3 and it was found that the effect of fertilizer application on the ambient NH₃ concentration was greatest in the month immediately following fertilizer application (highest ambient NH₃ concentration as 11.36㎍ m^-3). After that, it was expected that the NH₃ volatilization was promoted by increases in summer temperature and the concentration in the atmosphere was expected to increase. However, high NH₃ concentrations in the atmosphere were not observed due to strong rainfall that lasted for a long period. After that, the ambient NH₃ concentration gradually decreased through autumn and winter. In summary, when studying the contribution of fertilizer to the rate of domestic NH₃ emissions, it is necessary to look intensively for at least one month immediately after fertilizer application, and weather information such as precipitation and no-rain days should be considered in the field study.

• Journal of Wetlands Research
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• v.24 no.3
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• pp.204-212
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• 2022

The LID technique began to be applied in Korea after 2009, and LID facilities are installed and operated for rainwater management in business districts such as the Ministry of Environment, the Ministry of Land, Infrastructure and Transport, and LH Corporation, public institutions, commercial land, housing, parks, and schools. However, looking at domestic cases, the application cases and operation periods are insufficient compared to those outside the country, so appropriate design standards and measures for operation and maintenance are insufficient. In particular, LID facilities constructed using LID techniques need to maintain the environment inside LID facilities because hydrological and environmental effects are expressed by material circulation and energy flow. The LID facility is designed with the treatment capacity planned for the water circulation target, and the proper maintenance, vegetation, and soil conditions are periodically identified, and the efficiency is maintained as much as possible. In other words, the soil created in LID is a very important design element because LID facilities are expected to have effects such as water pollution reduction, flood reduction, water resource acquisition, and temperature reduction while increasing water storage and penetration capacity through water circulation construction. In order to maintain and manage the functions of LID facilities accurately, the current state of the facilities and the cycle of replacement and maintenance should be accurately known through various quantitative data such as soil contamination, snow removal effects, and vegetation criteria. This study was conducted to investigate the current status of LID facilities installed in Korea from 2009 to 2020, and analyze soil changes through the continuity and current status of LID facilities applied over the past 10 years after collecting soil samples from the soil layer. Through analysis of Saturn, organic matter, hardness, water contents, pH, electrical conductivity, and salt, some vegetation-type LID facilities more than 5 to 7 years after construction showed results corresponding to the lower grade of landscape design. Facilities below the lower level can be recognized as a point of time when maintenance is necessary in a state that may cause problems in soil permeability and vegetation growth. Accordingly, it was found that LID facilities should be managed through soil replacement and replacement.

• Journal of Navigation and Port Research
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• v.46 no.1
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• pp.1-10
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• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1341-1352
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• 2023

The normalized difference vegetation index (NDVI) derived from satellite images is a crucial tool to monitor forests and agriculture for broad areas because the periodic acquisition of the data is ensured. However, optical sensor-based vegetation indices(VI) are not accessible in some areas covered by clouds. This paper presented a synthetic aperture radar (SAR) based approach to retrieval of the optical sensor-based NDVI using machine learning. SAR system can observe the land surface day and night in all weather conditions. Radar vegetation indices (RVI) from the Sentinel-1 vertical-vertical (VV) and vertical-horizontal (VH) polarizations, surface elevation, and air temperature are used as the input features for an automated machine learning (AutoML) model to conduct the gap-filling of the Sentinel-2 NDVI. The mean bias error (MAE) was 7.214E-05, and the correlation coefficient (CC) was 0.878, demonstrating the feasibility of the proposed method. This approach can be applied to gap-free nationwide NDVI construction using Sentinel-1 and Sentinel-2 images for environmental monitoring and resource management.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.