• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.191-201
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• 2018

Recently, the frequency of heavy rainfall is increasing due to the effects of climate change, and heavy rainfall in urban areas has an unexpected and local characteristic. Floods caused by localized heavy rains in urban areas occur rapidly and frequently, so that life and property damage is also increasing. It is crucial how fast and precise observations can be made on successful flood management in urban areas. Local heavy rainfall is predominant in low-level storms, and the present large-scale radars are vulnerable to low-level rainfall detection and observations. Therefore, it is necessary to introduce a new urban flood forecasting system to minimize urban flood damage by upgrading the urban flood response system and improving observation and forecasting accuracy by quickly observing and predicting the local storm in urban areas. Currently, the WHAP (Water Hazard Information Platform) Project is promoting the goal of securing new concept water disaster response technology by linking high resolution hydrological information with rainfall prediction and urban flood model. In the WHAP Project, local rainfall detection and prediction, urban flood prediction and operation technology are being developed based on high-resolution small radar for observing the local rainfall. This study is expected to provide more accurate and detailed urban flood warning system by enabling high-resolution observation of urban areas.

• Journal of Conservation Science
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• v.35 no.3
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• pp.197-208
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• 2019

Biological damages of wooden cultural properties are closely related to the preservation of the environment; these damages can be accelerated because of rapid climate change. Therefore, to preserve cultural properties, it is important to understand environmental characteristics. This study aims to investigate the status of termite damage and the characteristics of major environmental factors such as micro-meteorology, meso-meteorology, and local-meteorology of the Josadang shrine in the Seonamsa temple at Suncheon. Damage was confirmed by visual observation and the response of the termite detection dog at the north-west corner. Also another damage was observed by the termite detection dog at the north-east corner. These pillars had lower surface temperature and higher moisture content compared with the pillars in the front. The mean temperature of the entire time was similar for the meteorologies; however, the relative humidity differed. High relative humidity, greater than 70%, was observed frequently. In particular, it was determined that the termite activity days were the most inside the Josadang shrine. The statistical analysis confirmed that there was a difference between the meteorology events through the F ratio. In addition, the difference of environmental factors with relative humidity and temperature was identified more great difference in relative humidity through the t-statistics of temperature and relative humidity. And then relative humidity was confirmed most great in the difference of meso-meteorology and local-meteorology.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Korean Journal of Agricultural Science
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• v.50 no.2
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• pp.299-312
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• 2023

The paddy environment is classified as a wetland and occupies a very large proportion of the freshwater environment. It is also ecologically important as a habitat and spawning ground for many aquatic insects and amphibian larvae. However, due to climate change and indiscriminate spraying of pesticides, the rice field ecosystem is continuously threatened. In order to restore ecologically damaged rice paddies in the future, information on organisms living in the rice paddy ecosystem, which can serve as a restoration standard, is needed. The eDNA metabarcoding analysis method is a very effective means of accumulating information on many organisms living in the rice field ecosystem because it can indirectly identify the existence of taxa that are no longer found in the target ecosystem due to different adult life periods or metamorphosis. In this study, genes of four species of frogs and nine species of aquatic insects were also discovered, and some taxa were directly discovered in the field. A large number of taxa have been discovered only by DNA searches, and traditional survey methods have only been able to identify very limited taxa. This eDNA-based paddy field biosearch is expected to be very useful in the investigation of biodiversity in agricultural ecosystems due to its strong analytical resolution.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.2
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• pp.159-168
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• 2018

Climate change is believed to increase the amount of dissolved organic matter in surface water, as a result of the release of bulk organic matter, which make difficult to achieve a high quality of drinking water via conventional water treatment techniques. Therefore, the natural water treatment techniques, such as managed aquifer recharge (MAR), can be proposed as a alternative method to improve water quality greatly. Removal of bulk organic matter using managed aquifer recharge system is mainly achieved by biodegradation. Biodegradable dissolved organic carbon (BDOC) and assimilable organic carbon (AOC) can be used as water quality indicators for biological stability of drinking water. In this study, we compared the change of BDOC and AOC with respect to pretreatment methods (i.e., ozone or peroxone). The oxidative pretreatment can transform the recalcitrant organic matter into readily biodegradable one (i.e., BDOC and AOC). We also investigated the differences of organic matter characteristics between BDOC and AOC. We observed the decreases in dissolved organic carbon (DOC) and the tryptophan-like fluorescence intensities. Liquid chromatographic - organic carbon detection (LC-OCD) analysis also showed the reduction of the low molecular weight (LMW) fraction (15% removed, less than 500 Da), which is known to be easily biodegradable, and the biopolymers, high molecular weight fractions (66%). Therefore, BDOC consists of a broad range of organic matter characteristics with respect to molecular weight. In AOC, low molecular weight organic matter and biopolymers fraction was reduced by 11 and 6%, respectively. It confirmed that biodegradation by microorganisms as the main removal mechanism in AOC, while BDOC has biodegradation by microorganism as well as the sorption effects from the sand. $O_3$ and $O_3+H_2O_2$ were compared with respect to biological stability and dissolved organic matter characteristics. BDOC and AOC were determined to be about 1.9 times for $O_3$ and about 1.4 times for $O_3+H_2O_2$. It was confirmed that $O_3$ enhanced the biodegradability by increasing LMW dissolved organic matter.

• Korean Journal of Heritage: History & Science
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• v.55 no.2
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• pp.102-111
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• 2022

Termites are a group of social insects that are one of the primary causes of damage to wooden architectural heritage. Since termite damage impairs the authenticity and structural stability of cultural heritage, it is imperative to prevent it. This study examines the extent of termite damage to wooden architectural heritage as part of efforts to prevent termite damage to nationally designated wooden architectural heritage sites across the country. The extent of termite damage to each cultural heritage was assessed qualitatively and quantitatively and comparatively analyzed by region using the results of the "Investigation on Biological Damage to Wooden Architectural Heritages" conducted by the National Research Institute of Cultural Heritage from 2016 to 2019. It involved 362 nationally designated wooden architectural heritages(25 national treasures, 157 treasures, 180 national folklore cultural heritages) and 1,104 buildings. The results were as follows: termite detection dogs reacted at 317(87.6%) of the 362 wooden heritages, with visible termite damage observed in 185 cases(51.1%). Furthermore, termite damage was confirmed using one of two methods(detection dogs or visual inspection) in 324 cases(89.5%). Of the 1,104 buildings, termite detection dogs reacted at 668(60.5%), while 339(30.7%) showed visible termite damage. Employing one of the two methods, damage was confirmed in 702 buildings(63.6%). The country was categorized into nine regions(Seoul Metropolitan Area, Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, and Jeju) to examine the termite damage rate and the degree of damage to each cultural heritage according to location. Termite detection dogs reacted to more than 70% of the cultural heritage in all regions. Visible damage was minimal in the Seoul metropolitan area(32.1%) and Gangwon(21.4%) but severe in Chungnam(65.6%), Jeonnam(67.3%), and Gyeongnam(68.2%). By quantifying the degree of termite damage of each cultural heritage as a ratio of the absence of termite damage among the total absence, the average termite damage of the cultural heritage across the country was 9.2%. Regional variance analysis showed that the cultural heritage in Jeonbuk and Jeonnam showed a statistically significantly higher degree of termite damage than the cultural heritage in the Seoul metropolitan area, Chungbuk, and Gyeongbuk. This paper comprehensively analyzed termite damage to nationally designated wooden architectural heritage. The findings are expected to be valuable in establishing policies for the preservation and management of cultural heritage sites in the future.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of the Korean earth science society
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• v.40 no.5
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• pp.502-517
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• 2019

Global warming and rapid climate change have long affected the characteristics of typhoons in the Northwest Pacific, which has induced increasing devastating disasters along the coastal regions of the Korean peninsula. Synthetic Aperature Radar (SAR), as one of the microwave sensors, makes it possible to produce high-resolution sea surface wind field around the typhoon under cloudy atmospheric conditions, which has been impossible to obtain the winds from satellite optical and infrared sensors. The Geophysical Model Functions (GMFs) for sea surface wind retrieval from SAR data requires the input of wind direction, which should be based on the accurate estimation of the center of the typhoon. This study estimated the typhoon centers using Sentinel-1A images to improve the problem of typhoon center detection method and to reflect it in retrieving the sea surface wind. The results were validated by comparing with the typhoon best track data provided by the Korea Meteorological Administration (KMA) and Japan Meteorological Agency (JMA), and also by using infrared images of Himawari-8 satellite. The initial center position of the typhoon was determined by using VH polarization, thereby reducing the possibility of error. The detected center showed a difference of 23.76 km on average with the best track data of the four typhoons provided by the KMA and JMA. Compared to the typhoon center estimated by Himawari-8 satellite, the results showed an average spatial variation of 11.80 km except one typhoon located near land with a large difference of 58.73 km. This result suggests that high-resolution SAR images can be used to estimate the center and retrieve sea surface wind around typhoons.