• Journal of Environmental Science International
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• v.31 no.10
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• pp.815-824
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• 2022

It is necessary to understand the amount of snowfall and area of snow cover of Mt. Halla to ensure the safety of mountaineers and to protect the ecosystem of Mt. Halla against climate change. However, there are not enough related studies and observation posts for monitoring snow load. Therefore, to supplement the insufficient data, this study proposes an analysis of snow load and snow cover using normalized-difference snow index. Using the images obtained from the Sentinel2 satellite, the normalized-difference snow index image of Mt. Halla could be acquired. This was examined together with the meteorological data obtained from the existing observatory to analyze the change in snow cover for the years 2020 and 2021. The normalized-difference snow index images showed a smaller snow pixel number in 2021 than that in 2020. This study concluded that 2021 may have been warmer than 2020. In the future, it will be necessary to continuously monitor the amount of snow and the snow-covered area of Mt. Halla using the normalized-difference snow index image analysis method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.77-88
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• 2022

This study aims to understand the relationship between the distribution of fish species in the two water ecosystems and the habitat factors according to the survey period targeting Gwanggyo Lake Park in the city. There are studies on the appearance and distribution of species by applying eDNA to freshwater ecosystems. However, in the domestic, streams are the target, and studies on the relationship between species distribution and habitat environment in two water environments are lacking. We conducted to analyze the species list and relationship with habitat factors using eDNA research in May and October at 21 points in Gwanggyo Lake Park, Suwon City, which were connected to lakes and streams. As a result, there was no species difference in the water environment according to the survey period. However, the total number of reads during the spawning season(May) was 3,126,482, which was more than double that after the spawning season(October). Tolerant species appeared in Woncheon Lake with a slow or stagnant flow, but there was no significant correlation between species and habitat factors depending on the survey period. On the other hand, intermediate and sensitive species appeared in the Woncheon stream with high flow. There was a significant correlation between the low temperature during the spawning season and the high dissolved oxygen content after the spawning season(P<0.001, Tem.: 20.7±2.6℃, DO: 8.6±1.7). It is expected that environmental DNA will be used to survey species and suggest monitoring methods according to the survey period.

• Korean small business review
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• v.43 no.4
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• pp.155-172
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• 2021

This research means that it analyzed the conflict structure of key stakeholders in the operation and management of the Regulation Free Zone. The analysis results are as follows. First, for the safety review related to the amendment of the law, the process of presenting a preliminary review opinion is additionally required. Second, institutional improvement is needed for the complicated preliminary preparation stage in the management system issue. Third, there is the issue of whether to provide an incentive structure to the local innovation ecosystem or to leave it to the autonomy of the participating companies and guarantee the choice in the post-management issue. In the future, this research suggests a method to systematically prepare a micro-policy demand identification process through continuous monitoring using the Q method.

• The Journal of Engineering Geology
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• v.32 no.2
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• pp.271-280
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• 2022

Landfast sea ice forms near coastlines in polar regions. Continuous monitoring of this sea ice is important, as it plays a key role in the marine ecosystem and affects the operation of nearby research stations. This study detected landfast sea ice around Jang Bogo research station in East Antarctica by stacking interferometric coherence images of Sentinel-1 synthetic aperture radar (SAR) data with 6-, 12- and 18-day temporal baselines. A total of 50 landfast sea ice maps were generated covering July 2017 to June 2018. The time series revealed regional differences in the timing of the maximum extent as well as growth rate of landfast sea ice. Overall, detecting landfast sea ice using interferometric SAR coherence seems promisingly feasible; however, limitations remain owing to low backscattering coefficients from new and smooth sea ice surfaces and subtle movements of sea ice in contact with the Campbell Glacier Tongue.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.1
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• pp.30-36
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• 2022

We collected a total of four butterfly ray specimens (Gymnura japonica, 213.4-695.0 mm in total length) in Korea from 2016 to 2021 and investigated their morphological and molecular characteristics in order to clarify their taxonomic status. These features are summarized as follows. Disc lozenge-shaped, 1.8-2.0 times broader than long. Tail very short, post-cloaca length 23.9-28.2% in disc width. Snout short, no rostral cartilage. Clasper short, no hook. Dorsal surface uniform yellow or brownish grey, with or without rounded light yellow spots. An analysis of 434 base-pair sequences of mitochondrial DNA cytochrome c oxidase subunit I showed that all four specimens corresponded to G. japonica from Japan (Kimura-2-parameter distance = 0-0.2%), suggesting that the color patterns found may be due to intraspecific color variation. G. japonica resembles Gymnura poecilura but differs in that it has a shorter tail length to disc width (23.9-28.2% in G. japonica vs. 40.1-48.3% in G. poecilura). This study revealed that G. japonica occurred in areas affected by the Tsushima Warm Current, tentatively suggesting that G. japonica may be an indicator species for monitoring marine ecosystem changes due to climate change.

• Economic and Environmental Geology
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• v.56 no.2
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• pp.185-199
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• 2023

This study aimed to predict the effects of water ecology on the supply of hydrothermal energy to model a housing complex in Eco Delta Smart Village in Busan. Based on the results, engineering measures were recommended to minimize problems due to possible temperature variations on the supply of hydrothermal energy from the river. The current distribution of fish, benthic macroinvertebrates, and phytoplankton in the Pyeonggang Stream was monitored to determine their effects on water ecology. In the research area, five species and three families of fish were observed. The dominant species was Lepomis macrochirus, and the subdominant species was Carassius auratus. Twenty-five species and 21 families of benthic macroinvertebrates were found. The distribution of aquatic insects was poor in this area. The dominant species were Chironomidae sp., Lymnaea auricularia, Appasus japonicus, and Caridina denticulata denticulata in February, May, July, and October. Dominant phytoplankton were Aulacoseira ambigua and Nitzschia palea in February and May. Microcystis sp. was dominant in July and October. The health of the ecology the Pyeonggang Stream was assessed as D (bad) according to the benthic macroinvertebrate index (BMI). Shifts in the location of the discharge point 150 m downstream from intake points and discharge through embedded rock layer after adding equal amounts of stream water as was taken at the beginning were suggested to minimize water temperature variations due to the application of hydrothermal energy. When the scenario (i.e., quantity of water intake and dilution water, 1,600 m³/d and water temp. difference ±5 ℃) was realized, variations in water temperature were assessed at -0.19 ℃ and 0.59 ℃ during cooling and heating, respectively, at a point 10 m downstream. Water temperatures recorded at -0.20 ℃ and 0.68 ℃ during cooling and heating, respectively, at a point 10 m upstream. All stream water temperatures after the application of hydrothermal energy recovered within 24 hours. Future work on the long-term monitoring of ecosystems is suggested, particularly to analyze the influence of the water environment on hydrothermal energy supply operations.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.183-183
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• 2023

Smart water cities (SWC) are urban municipalities that utilizes modern innovations in managing and preserving the urban water cycle in the city; with the purpose of securing sustainability and improving the quality of life of the urban population. Understanding the different urban water characteristics and management strategies of cities situate a baseline in the development of evaluation scheme in determining whether the city is smart and sustainable. This research herein aims to develop measurements and evaluation for SWC Key Performance Indicators (KPIs), and set up a unified global standard and certification scheme. The assessment for SWC is performed in technical, as well as governance and prospective aspects. KPI measurements under Technical Pillar assess the cities' use of technologies in providing sufficient water supply, monitoring water quality, strengthening disaster resilience, minimizing hazard vulnerability, and maintaining and protecting the urban water ecosystem. Governance and Prospective Pillar on the other hand, evaluates the social, economic and administrative systems set in place to manage the water resources, delivering water services to different levels of society. The performance assessment is composed of a variety of procedures performed in a quantitative and qualitative manner, such as computations through established equations, interviews with authorities in charge, field survey inspections, etc. The developed SWC KPI measurements are used to evaluate the urban water management practices for Busan Eco Delta city, a Semulmeori waterfront area in Gangseo district, Busan. The evaluation and scoring process was presented and established, serving as the basis for the application of the smart water city certification all over the world. The established guideline will be used to analyze future cities, providing integrated and comprehensive information on the status of their urban water cycle, gathering new techniques and proposing solutions for smarter measures.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.86-94
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• 2023

Climate change is more rapid in the Arctic than elsewhere in the world, and increased precipitation and warming are expected cause changes in biogeochemical processes due to altered microbial communities and activities. It is crucial to investigate microbial responses to climate change to understand changes in carbon and nitrogen dynamics. We investigated the effects of increased temperature and precipitation on microbial biomass and community structure in dry tundra using two depths of soil samples (organic and mineral layers) under four treatments (control, warming, increased precipitation, and warming with increased precipitation) during the growing season (June-September) in Cambridge Bay, Canada (69°N, 105°W). A phospholipid fatty acid (PLFA) analysis method was applied to detect active microorganisms and distinguish major functional groups (e.g., fungi and bacteria) with different roles in organic matter decomposition. The soil layers featured different biomass and community structure; ratios of fungal/bacterial and gram-positive/-negative bacteria were higher in the mineral layer, possibly connected to low substrate quality. Increased temperature and precipitation had no effect in either layer, possibly due to the relatively short treatment period (seven years) or the ecosystem type. Mostly, sampling times did not affect PLFAs in the organic layer, but June mineral soil samples showed higher contents of total PLFAs and PLFA biomarkers for bacteria and fungi than those in other months. Despite the lack of response found in this investigation, long-term monitoring of these communities should be maintained because of the slow response times of vegetation and other parameters in high-Arctic ecosystems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1873-1893
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• 2023

The development of lightweight, low energy and small-sized sensors incorporated with the wireless networks has brought about a phenomenal growth of Wireless Sensor Networks (WSNs) in its different fields of applications. Moreover, the routing of data is crucial in a wide number of critical applications that includes ecosystem monitoring, military and disaster management. However, the time-delay, energy imbalance and minimized network lifetime are considered as the key problems faced during the process of data transmission. Furthermore, only when the functionality of cluster head selection is available in WSNs, it is possible to improve energy and network lifetime. Besides that, the task of cluster head selection is regarded as an NP-hard optimization problem that can be effectively modelled using hybrid metaheuristic approaches. Due to this reason, an Improved Coyote Optimization Algorithm-based Clustering Technique (ICOACT) is proposed for extending the lifetime for making efficient choices for cluster heads while maintaining a consistent balance between exploitation and exploration. The issue of premature convergence and its tendency of being trapped into the local optima in the Improved Coyote Optimization Algorithm (ICOA) through the selection of center solution is used for replacing the best solution in the search space during the clustering functionality. The simulation results of the proposed ICOACT confirmed its efficiency by increasing the number of alive nodes, the total number of clusters formed with the least amount of end-to-end delay and mean packet loss rate.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1577-1589
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• 2023

Recently, the necessity of predicting changes for monitoring ocean is widely recognized. In this study, we performed a time series prediction of remote-sensing reflectance (Rrs), which can indicate changes in the ocean, using Geostationary Ocean Color Imager (GOCI) data. Using GOCI-I data, we trained a multi-scale Convolutional Long-Short-Term-Memory (ConvLSTM) which is proposed in this study. Validation was conducted using GOCI-II data acquired at different periods from GOCI-I. We compared model performance with the existing ConvLSTM models. The results showed that the proposed model, which considers both spatial and temporal features, outperformed other models in predicting temporal trends of Rrs. We checked the temporal trends of Rrs learned by the model through long-term prediction results. Consequently, we anticipate that it would be available in periodic change detection.