• Economic and Environmental Geology
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• v.54 no.6
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• pp.699-707
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• 2021

Hwajinpo Lagoon, located on the eastern coast of Korea, is a unique environment where freshwater and saltwater are mixed. Systematic management of the lagoon is required because it is a biodiversity-rich and area of high conservation value. The existing environment of the lagoon was evaluated by identifying the distribution of the groundwater level and groundwater flow characteristics. In addition, hydrogeochemical fluctuations were analyzed to determine the effect of seawater intrusion into the aquifer. The results demonstrate that the freshwater-saltwater interface is distributed throughout the aquifer and rises when water of the lagoon evaporates due to prolonged periods of low rainfall and high temperature, thereby increasing the possibility of seawater inflow through groundwater. As for the ionic delta properties (difference between the measured and theoretical concentration of mixed waters), it was estimated that the cation-exchange and precipitation reactions occurred in the aquifer due to seawater intrusion. The ratio of seawater mixed at each point was calculated, using oxygen isotopes and chloride as tracers, resulting in an average of 0.3 and a maximum of 0.87. The overall seawater mixing ratio appears to be distributed according to the distance from the coast. However, some of the results were deviated from the theoretical expectations and reflected the characteristics of the nearby aquifers. Further research on seasonal changes and simulation of seawater intrusion mechanisms is required for specific analysis.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.209-219
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• 2022

To experimentally investigate the variation of soil characteristics in slope during rainfall and the shape of slope failure, the model test was performed using soil box and artificial rainfall simulator. The model test of slope formed by the homogenous sand was performed, and the saturation pattern in the model slope due to rainfall infiltration was observed. The slope model with the inclination of 35° was set up on the slope of 30°, and the rainfall intensity of 50 mm/hr was applied in the test. The soil depth of 35 cm was selected by considering the size of soil box, and the TDR (time domain reflectometry) sensors were installed at various depths to investigate the change of soil characteristics with time. As the result of model test, the slope model during rainfall was saturated from the soil surface to the subsurface, and from the toe part to the crest part due to rainfall infiltration. That is, the toe part of slope was firstly saturated by rainfall infiltration, and then due to continuous rainfall the saturation range was enlarged from the toe part to the crest part in the slope model. The failure of slope model was started at the toe part of slope and then enlarged to the crest part, which is called as the retrogressive failure. At the end of slope failure, the collapsed area increased rapidly. Also, the mode of slope failure was rotational. Meanwhile, the slope failure was occurred when the matric suction in the slope was reached to the air entry value (AEV) estimated in soil-water characteristic curve (SWCC).

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• Land and Housing Review
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• v.13 no.3
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• pp.125-140
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• 2022

Road Deposited Sediment (RDS) is the solids formed from the wear of road, wear of vehicles, exhausts, and the input of the emissions from various sources out of the roads. RDS is seriously polluted by organic matter, nutrients, and metals. RDS plays an important role as the sink and the transport medium of the associated pollutants because RDS can be carried to the adjacent water system via stormwater runoff. In this regard, the heavy metals in RDS were investigated based on the publications. The contents of the metals in RDS were highly variable. The concentration of Cr, Ni, Cu, Fe, Zn, As, Cd, and Pb in urban RDS in various regions was in a range of 3.16-3,410, 1.15-1,382, 20.2-9,069, 2,980-124,853, 81-2,550, 2.3-214, 0.19-21.3, and 15.21-1,125 mg/kg, respectively. The anthropogenic enrichment of the metals in RDS was confirmed by the high concentration of Cu, Zn, Cd, and Pb. The contents of the metals were higher in industrial and traffic areas than in residential areas, while they were generally increased with decreasing particle size. It is believed that this study's results would contribute to quantifying the metals' load via RDS and establishing control strategies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.135-144
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• 2022

Since vegetation provides humans with various ecological spaces and is also very important in terms of water resources and climatic environment, many vegetation monitoring studies using vegetation indexes based on near infrared sensors have been conducted. Therefore, if the near infrared sensor is not provided, the vegetation monitoring study has a practical problem. In this study, to improve this problem, the NDVI (Normalized Difference Vegetation Index) was used as a reference to evaluate the accuracy of the vegetation index based on the optical sensor. First, the Kappa coefficient was calculated by overlapping the vegetation survey point surveyed in the field with the NDVI. As a result, the vegetation area with a threshold value of 0.6 or higher, which has the highest Kappa coefficient of 0.930, was evaluated based on optical sensor based vegetation index accuracy. It could be selected as standard data. As a result of selecting NDVI as reference data and comparing with vegetation index based on optical sensor, the Kappa coefficients at the threshold values of 0.04, 0.08, and 0.30 or higher were the highest, 0.713, 0.713, and 0.828, respectively. In particular, in the case of the RGBVI (Red Green Red Vegetation Index), the Kappa coefficient was high at 0.828. Therefore, it was found that the vegetation monitoring study using the optical sensor is possible even in environments where the near infrared sensor is not available.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.277-286
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• 2021

Background: As trade increases, the influx of various alien species and their spread to new regions are prevalent and no longer a special problem. Anthropogenic activities and climate changes have made the distribution of alien species out of their native range common. As a result, alien species can be easily found anywhere, and they have nothing but only a few differences in intensity. The prevalent distribution of alien species adversely affects the ecosystem, and a strategic management plan must be established to control them effectively. To this end, hot spots and cold spots were analyzed according to the degree of distribution of invasive alien plants, and major environmental factors related to hot spots were found. We analyzed the 10,287 distribution points of 126 species of alien plants collected through the national survey of alien species by the hierarchical model of species communities (HMSC) framework. Results: The explanatory and fourfold cross-validation predictive power of the model were 0.91 and 0.75 as AUC values, respectively. The hot spots of invasive plants were found in the Seoul metropolitan area, Daegu metropolitan city, Chungcheongbuk-do Province, southwest shore, and Jeju island. Generally, the hot spots were found where the higher maximum temperature of summer, precipitation of winter, and road density are observed, but temperature seasonality, annual temperature range, precipitation of the summer, and distance to river and sea were negatively related to the hot spots. According to the model, the functional traits accounted for 55% of the variance explained by the environmental factors. The species with higher specific leaf areas were more found where temperature seasonality was low. Taller species preferred the bigger annual temperature range. The heavier seed mass was only preferred when the max temperature of summer exceeded 29 ℃. Conclusions: In this study, hot spots were places where 2.1 times more alien plants were distributed on average than non-hot spots (33.5 vs 15.7 species). The hot spots of invasive plants were expected to appear in less stressful climate conditions, such as low fluctuation of temperature and precipitation. Also, the disturbance by anthropogenic factors or water flow had positive influences on the hot spots. These results were consistent with the previous reports about the ruderal or competitive strategies of invasive plants instead of the stress-tolerant strategy. The functional traits are closely related to the ecological strategies of plants by shaping the response of species to various environmental filters, and our result confirmed this. Therefore, in order to effectively control alien plants, it is judged that the occurrence of disturbed sites in which alien plants can grow in large quantities is minimized, and the river management of waterfronts is required.

• Journal of Environmental Impact Assessment
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• v.31 no.4
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• pp.241-249
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• 2022

Humans and wild birds coexist in cities, where habitat fragmentation due to urbanization threatens the habitat and movement of birds. In this study, in order to identify landscape features associated with wild bird collide, we characterized landscape composition within a 500 m radius and points of wild bird carcasses in Suwon-city, South Korea. Dead birds were identified as having a Normalized Difference Vegetation Index (NDVI) of 0.3, Normalized Difference Built-up Index (NDBI) of -0.05, and Normalized Difference Water Index (NDWI) of -0.16 at the points of collide. And there were NDVI of 0.34, NDBI of -0.01, NDWI of -0.18, building height of 13.8 m, and soundproof wall length of 227.3 m within a radius of 500 m. Land cover type was dominated by grassland, used area, and bare land. In particular, the edges of urbanized areas, where apartments bordered forests, reservoirs, and golf courses, were identified as high-risk spaces. In order to minimize bird mortality risk in urban environments, the impact of changes to a vertical landscape should be reviewed from an environmental impact assessment approach. In addition, a preventive management plan that considers the temporal and spatial features that wild animals can safely avoid and adapt to in urbanized spaces should be prepared.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.473-488
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• 2022

To have a better understanding of the impact of the PETRONAS oil and gas platform on commercial fisheries activities, Universiti Malaysia Terengganu (UMT) examined two approaches which are data collection from satellite and data collection from fishermen and anglers. By profiling the anglers who utilize reefed oil and gas structures for fishing, it can determine if the design and location of the reef platforms will benefit or negatively impacts those anglers and fisherman. Furthermore, this assessment will be contributing to the knowledge regarding the value of offshore oil and gas platforms as fisheries resources. Collectively, the apparent fishing activity data included, combined with the findings in the reefing viability index will help to inform PETRONAS's future decommissioning decisions and may help determine if the design and proposed locations for future rigs-to-reefs candidates would benefit commercial fishing groups, further qualifying them as appropriate artificial reef candidates. The method applied in this study is approaching by using a data satellite known as Google's Global Fishing Watch technology, which is one of the applications to measure commercial fishing efforts around the globe. The apparent commercial fishing effort around the selected twelve PETRONAS platforms was analyzed from January 2012 to December 2018. Using the data collection from fishermen which is the total estimation of commercial fish value cost (in Malaysia ringgit, MYR [RM]) in Peninsular Malaysia Asset, Sabah Asset, and Sarawak Operation region. The data were extracted every month from 2016 to 2018 from the National Oceanic and Atmospheric Administration database. Most of the selected platforms that show a high frequency of vessels around the year are platform KP-A, platform BG-A and platform PL-B. The estimated values of commercial fishes varied between platforms, with ranged from RM 10,209.92 to RM 89,023.78. Thus, platforms with high commercial fish value are selected for reefing in-situ and will serve multi-purposes and benefit the locals as well as the country. The current study has successfully assessed the potential reefing area of the Malaysian offshore environment with greater representativeness and this paper focused on its potential as a new fishing ground.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.413-419
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• 2022

As the development of the underground space becomes active, safety accidents related to the underground are frequently occurring in recent years. In this regard, the Ministry of Land, Infrastructure and Transport is enforcing the 『Special Act on Underground Safety Management』 (enforced on January 1, 2018, hereafter referred to as the Underground Safety Act). Among the core contents of the Underground Safety Act, underground facilities(water supply, sewage, gas, power, communication, heating) buried underground, underground structures(subway, underpass, underpass, underground parking lot, underground shopping mall, common area), ground (Drilling, wells, geology) of 15 types of underground information can be checked at a glance on a three-dimensional basis by constructing an integrated underground spatial map and using it. The purpose of this study is to develop a program that can quickly inspect the three-dimensional model after creating a three-dimensional underground structure data among the underground spatial integration maps. To this end, we first investigated and reviewed the domestic and foreign status of technology that generates and automatically inspects 3D underground structure data. A quality inspection program was developed. Through this study, it is judged that it will be meaningful as a basic research for improving the quality of underground structures on the integrated map of underground space by automating more than 98% of the 3D model inspection process, which is currently being conducted manually.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.179-189
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• 2022

Ice and water droplets rise and fall above the freezing altitude under the effects of strong updrafts and downdrafts, grow into hail, and then fall to the ground in the form of balls or irregular lumps of ice. Although such hail, which occurs in a local area within a short period of time, causes great damage to the agricultural and forestry sector, there is a paucity of domestic research toward predicting hail. The objective of this study was to introduce Land-Atmosphere Modeling Package (LAMP) hail prediction and measure its performance for 50 hail events that occurred from January 2020 to July 2021. In the study period, the frequency of occurrence was high during the spring and during afternoon hours. The average duration of hail was 15 min, and the average diameter of the hail was 1 cm. The results showed that LAMP predicted hail events with a detection rate of 70%. The hail prediction performance of LAMP deteriorated as the hail prediction time increased. The radar reflectivity of actual cases of hail indicated that the average maximum reflectivity was greater than 40 dBZ regardless of altitude. Approximately 50% of the hail events occurred when the reflectivity ranged from 30~50 dBZ. These results can be used to improve the hail prediction performance of LAMP in the future. Improved hail prediction performance through LAMP should lead to reduced economic losses caused by hail in the agricultural and forestry sector through preemptive measures such as net coverings.