• Journal of Environmental Impact Assessment
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• v.27 no.3
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• pp.267-278
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• 2018

With climate change and population growth, there are significant increases in water scarcity. There have been water security assessments to abate the gap between water demand and availability to support water resource management. However, most of the assessments are focusing on the water that flows through either on or below the land surface, failing to consider water that infiltrates and can be used by vegetation. This study presents water scarcity assessment accounting for Blue and Green water concept, and applied the method to Boryung region. Monthly streamflow, evapotranspiration, and soil moisture were estimated by SWAT modeling, and each of them was used to analyze Blue and Green water scarcity. Blue and Green water scarcity had different aspect, and the result indicated the time when water scarcity is more likely to happen. The water scarcity assessment framework presented in this paper provides novel assessment method integrating hydrologic and ecosystem aspects, thereby improving the understanding of how water resources should be managed.

• Ecology and Resilient Infrastructure
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• v.9 no.2
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• pp.83-92
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• 2022

The 2020 summer extreme flood severely disturbed the riparian ecosystem of the Seomjin River. Some trees were killed by the flood impact, whereas others have recovered through epicormic regeneration after the disturbance. At the same time, several tree individuals newly germinated. This research aimed to explain the recovery of the riparian ecosystem by spatial proximity between each tree individual of different characteristics, such as "dead", "recovered", and "newly germinated". A spatial point pattern analysis based on K and g-functions revealed that the newly germinated trees and the existing trees were distributed in the spatially clumping patterns. However, further detailed analysis revealed that the new trees were statistically less attracted to the recovered trees than the dead trees, implying competitive interactions hidden in the facilitative interactions. Habitat amelioration by the existing trees positively affected the growth of the new trees, while "living" existing trees were competing with the new trees for resources. This research is expected to provide new knowledge in this era of rapid climate change, which likely induces stronger and more frequent natural disturbance than before. Environmental factors have been widely used for ecosystem modeling, but species interactions, represented by the relative spatial distribution of plant individuals, are also valuable factors explaining ecosystem dynamics.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.82-98
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• 2019

The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.236-256
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• 2011

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.2
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• pp.109-117
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• 2013

The Global Framework on Climate Services (GFCS) will guide the development of climate services that link science-based climate information and predictions with climate-risk management and adaptation to climate change. GFCS structure is made up of 5 pillars; Observations/Monitoring (OBS), Research/ Modeling/ Prediction (RES), Climate Services Information System (CSIS) and User Interface Platform (UIP) which are all supplemented with Capacity Development (CD). Corresponding to each GFCS pillar, the Commission for Agricultural Meteorology (CAgM) has been proposing "Global Initiatives in AgroMeteorology" (GIAM) in order to facilitate GFCS implementation scheme from the perspective of AgroMeteorology - Global AgroMeteorological Outlook System (GAMOS) for OBS, Global AgroMeteorological Pilot Projects (GAMPP) for RES, Global Federation of AgroMeteorological Society (GFAMS) for UIP/RES, WAMIS next phase for CSIS/UIP, and Global Centers of Research and Excellence in AgroMeteorology (GCREAM) for CD, through which next generation experts will be brought up as virtuous cycle for human resource procurements. The World AgroMeteorological Information Service (WAMIS) is a dedicated web server in which agrometeorological bulletins and advisories from members are placed. CAgM is about to extend its service into a Grid portal to share computer resources, information and human resources with user communities as a part of GFCS. To facilitate ICT resources sharing, a specialized or dedicated Data Center or Production Center (DCPC) of WMO Information System for WAMIS is under implementation by Korea Meteorological Administration. CAgM will provide land surface information to support LDAS (Land Data Assimilation System) of next generation Earth System as an information provider. The International Society for Agricultural Meteorology (INSAM) is an Internet market place for agrometeorologists. In an effort to strengthen INSAM as UIP for research community in AgroMeteorology, it was proposed by CAgM to establish Global Federation of AgroMeteorological Society (GFAMS). CAgM will try to encourage the next generation agrometeorological experts through Global Center of Excellence in Research and Education in AgroMeteorology (GCREAM) including graduate programmes under the framework of GENRI as a governing hub of Global Initiatives in AgroMeteorology (GIAM of CAgM). It would be coordinated under the framework of GENRI as a governing hub for all global initiatives such as GFAMS, GAMPP, GAPON including WAMIS II, primarily targeting on GFCS implementations.

• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.24-36
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• 2021

Countries around the world, including the Republic of Korea, are participating in efforts to preserve biodiversity. Concerning species, in particular, studies that aim to find potential habitats and establish conservation plans by conducting habitat suitability analysis for specific species are actively ongoing. However, few studies on mid- to long-term changes in suitable habitat areas are based on accumulated information. Therefore, this study aimed to analyze the time-series changes in the habitat suitable area and examine the otters' changing pattern (Lutra lutra) designated as Level 1 endangered wildlife in Gangwon-do. The time-series change analysis used the data on otter species' presence points from the 2nd, 3rd, and 4th national natural environment surveys conducted for about 20 years. Moreover, it utilized the land cover map consistent with the survey period to create environmental variables to reflect each survey period's habitat environment. The suitable habitat area analysis used the MaxEnt model that can run based only on the species presence information, and it has been proven to be reliable by previous studies. The study derived the habitat suitability map for otters in each survey period, and it showed a tendency that habitats were distributed around rivers. Comparing the response curves of the environmental variables derived from the modeling identified the characteristics of the habitat favored by otters. The examination of habitats' change by survey period showed that the habitats based on the 2nd National Natural Environment Survey had the widest distribution. The habitats of the 3rd and 4th surveys showed a tendency of decrease in area. Moreover, the study aggregated the analysis results of the three survey periods and analyzed and categorized the habitat's changing pattern. The type of change proposed different conservation plans, such as field surveys, monitoring, protected area establishment, and restoration plan. This study is significant because it produced a comprehensive analysis map that showed the time-series changes of the location and area of the otter habitat and proposed a conservation plan that is necessary according to the type of habitat change by region. We believe that the method proposed in this study and its results can be used as reference data for establishing a habitat conservation and management plan in the future.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.669-680
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• 2013

Ozone sensitivity analysis with respect to $NO_x$ is conducted around the south-eastern area of the Korean Peninsula. WRF-CMAQ modeling system is used to simulate a local circulation and high ozone episode day. To analyze the sensitivity, the adjoint model for CMAQ is adopted in this study. The purpose of current study is to investigate the location that affects a day time ozone concentration of these receptors on the high ozone episode day. Adjoint sensitivity analysis for Daegu shows two areas of influence. One is the range from the neighboring location to Pohang and it affects mainly on the same day as receptor time. The other is the remote south-eastern area from Daegu. This remote influence area suggests that $NO_x$ emitted on the previous day can change the ozone concentration at receptor time. The influence area for Busan, on the other hand, is originated only from the emission on the previous day because the sea-breeze occurred on the episode day makes low influence of surrounding emission. The cross sectional analysis reveals that $NO_x$ advection is important not only near the surface of land but also around the height of boundary layer.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of the Korea Institute of Building Construction
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• v.9 no.4
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• pp.119-129
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• 2009

Building construction trends have been changed dramatically in terms of size and mass. With the need to maximize land usage, there has been an increase in the construction of high-rise buildings. This affects not only the entire construction duration and cost, but also subsequent construction activities, such as work to increase underground facilities and in reclamation land area construction. These types of site conditions require soft ground reinforcement and the proper uplift water pressure treatment. In general, two kinds of methods have been used for uplift water pressure treatment systems. However, there have been some problems arising as the result of a lack of research and analysis on underground construction techniques, and a reliance on experiments over actual survey and analysis of site conditions. This paper focused on the problems of conventional selection procedure, by analyzing drawings and proposing a kind of modeling for a reasonable procedure. The results were applied to OO project as a sample construction case to be verified in this research. The initial plan in the case project was the Rock Anchor System. However, as there were terrible miscalculations of basic site conditions that had an extraordinary influence on the underground water level, such as the site's proximity to the Han-river, it was necessary to change the plan to include apermanent drainage system. This achieved a direct construction cost reduction \ 406,702,000 and a maximum sayings of 4% of operational cost, based on the 50-year building Life Cycle Cost.

• Korean Chemical Engineering Research
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• v.49 no.2
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• pp.187-194
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• 2011

In compliance with an international law about the ocean dumping of the sludge, the proper sewage treatment process which occurs from the wastewater treatment process has been becoming problem. Generally the sewage and the sludge are controlled from anaerobic condition when the sewage is treated and land filled, where the methane$(CH_{4})$ and the nitrous oxide $(N_{2}O)$ from this process are discharged. Because these gases have been known as one of the responsible gases for global warming, the wastewater treatment process is become known as emission sources of green house gases(GHG). This study is to suggest a new approach of estimate and environmental assessment of greenhouse gas emissions and sludge emissions from wastewater treatment processes. It was carried out by calculating the total amounts of GHG emitted from biological wastewater treatment process and the amount of the sludgegenerated from the processes. Four major biological wastewater treatment processes which are Anaerobic/Anoxic/Oxidation$(A_{2}O)$, Bardenpho, Virginia Initiative Plant(VIP), University of Cape Town(UCT)are used and GPS-X software is used to model four processes. Based on the modeling result of four processes, the amounts of GHG emissions and the sludge produced from each process are calculated by Intergovernmental Panel on Climate Change(IPCC) 2006 guideline report. GHG emissions for water as well as sludge treatment processes are calculated for environmental assessment has been done on the scenario of various sludge treatments, such as composting, incineration and reclamation and each scenario is compared by using a unified index of the economic and environmental assessment. It was found that Bardenpho process among these processes shows a best process that can emit minimum amount of GHG with lowest impact on environment and composting emits the minimum amount of GHG for sludge treatment.