• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.637-643
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• 2020

In this study, the information from environmental impact statements was converted into spatial data because environmental data from development sites are collected during the environmental impact assessment (EIA) process. Spatiotemporal big data were built from environmental spatial data for each environmental medium for 2,235 development sites during 2007-2018, available from public data portals. Comparing air-quality monitoring stations, 33,863 measurement points were constructed, which is approximately 75 times more measurement points than that 452 in Air Korea's real-time measurement network. Here, spatiotemporal big data from 2,677,260 EIAs were constructed. In the future, such data might be used not only for EIAs but also for various spatial plans.

• Environmental Engineering Research
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• v.14 no.2
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• pp.102-110
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• 2009

Application of artificial intelligence (AI) approaches in eco-environmental modeling has gradually increased for the last decade. Comprehensive understanding and evaluation on the applicability of this approach to eco-environmental modeling are needed. In this study, we reviewed the previous studies that used AI-techniques in eco-environmental modeling. Decision Tree (DT) and Artificial Neural Network (ANN) were found to be major AI algorithms preferred by researchers in ecological and environmental modeling areas. When the effect of the size of training data on model prediction accuracy was explored using the data from the previous studies, the prediction accuracy and the size of training data showed nonlinear correlation, which was best-described by hyperbolic saturation function among the tested nonlinear functions including power and logarithmic functions. The hyperbolic saturation equations were proposed to be used as a guideline for optimizing the size of training data set, which is critically important in designing the field experiments required for training AI-based eco-environmental modeling.

• Asia pacific journal of information systems
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• v.8 no.2
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• pp.1-18
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• 1998

As the management and preservation of the environment become an important social issue, information required to support environmental task is required. So, there is an increasing demand for environmental information and appropriate systems to manage it. The vast volume of environmental data is distributed in different knowledge domains and systems. Environmental data objects have the complex structure containing environmental quality data and attribute data. Environmental information systems must be able to address these properties. This research has aimed at constructing well-defined schema design of environmental data, and making system architecture that environmental data kept by authorities should be made available to the public user. There are 3 major components in environmental information systems architecture ; User interface, Catalog libraries, Communication Provider. Web browsers provide consistent and intuitive user interfaces on Internet. The communication provider is a collection of diverse CGI functions. The main roles of the CGIs are to build interfaces between the Web, databases. Catalog libraries is libraries of various matadata including administration matadata. Administration matadata support the environmental administration and the managerial aspects of environmental data rather than explain a database itself or its properties.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.557-566
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• 2005

Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper we used k-means clustering of several clustering techniques. The k-means Clustering Is classified as a partitional clustering method. We analyze 2002 Gyeongnam social indicator survey data using k-means clustering techniques for environmental information. We can use these outputs given by k-means clustering for environmental preservation and environmental improvement.

• Environmental Analysis Health and Toxicology
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• v.30 no.sup
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• pp.4.1-4.7
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• 2015

Objectives Approximately 2000 phase-in substances are subject to registration according to the Act on the Registration and Evaluation, etc. of Chemical Substances (K-REACH), and the expected testing cost is 2.06 trillion Korean won assuming all the test data required for registration are acquired. The extent to which these enormous test costs can be reduced depends on the availability of existing data that can be used to meet the requirements of the K-REACH we examined the current availability of test data that can be used for chemical substance registration. Methods We analyzed the possibility of utilizing the existing test data obtained from 16 reference databases for 369 of 518 kinds of phase-in substances subject to registration that were reported in last October 2014. Results The physical and chemical properties were available for 57.1% of substances, whereas data regarding human hazards and environmental hazards were available at considerably lower rates, 8.5% and 11.8%, respectively. Conclusions Physical and chemical properties were available for a fairly high proportion, whereas human hazards and environmental hazards were reported for considerably fewer substances.

• Journal of Environmental Impact Assessment
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• v.22 no.6
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• pp.609-626
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• 2013

Air quality models have been widely used to study and simulate many air quality issues. In the simulation, it is important to raise the accuracy of meteorological predicted data because the results of air quality modeling is deeply connected with meteorological fields. Therefore in this study, we analyzed the effects of meteorological fields on the air quality simulation. This study was designed to evaluate MM5 predictions by using different initial condition data and different observations utilized in the data assimilation. Among meteorological scenarios according to these input data, the results of meteorological simulation using National Centers for Environmental Prediction (Final) Operational Global Analysis data were in closer agreement with the observations and resulted in better prediction on ozone concentration. And in Seoul, observations from Regional Meteorological Office for data assimilations of MM5 were suitable to predict ozone concentration. In other areas, data assimilation using both observations from Regional Meteorological Office and Automatical Weather System provided valid method to simulate the trends of meteorological fields and ozone concentrations. However, it is necessary to vertify the accuracy of AWS data in advance because slightly overestimated wind speed used in the data assimilation with AWS data could result in underestimation of high ozone concentrations.

• 한국데이터정보과학회:학술대회논문집
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• 2004.10a
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• pp.77-86
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• 2004

Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper we used k-means clustering of several clustering techniques. The k-means Clustering is classified as a partitional clustering method. We analyze 2002 Gyeongnam social indicator survey data using k-means clustering techniques for environmental information. We can use these outputs given by k-means clustering for environmental preservation and environmental improvement.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.280.1-285
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• 1998

The earth's environmental problems have attracted serious attention worldwide. Various kinds of environmental data, such as remote sensing data, have become available for examining. Although this data is crucial to understanding such problems, there has become an over-abundance in variety of size, format, and filetype which makes it difficult for researchers to handle. We feel that earth environmental researchers should not be burdened by such cumbersome tasks. Therefore, we are developing a digital library for earth environmental information and a VRML based data visualization system for it. Even now, content-based image retrieval systems have many problems attributed to the degree of difficulty in implementing them. Thus, we are trying to visualize this data so that researchers can utilize it more efficiently, effectively, and easily. A great advantage for VRML users is that people can see environmental data from any perspective above the earth and with any resolution easily. Also by using MPEG-movie, users can observe the changes of data drawn from time series files.

• Journal of Environmental Science International
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• v.29 no.10
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• pp.981-988
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• 2020

This study presents meteorological data integrity to improve environmental quality assessment in Yongdam catchment. The study examines both extreme ranges of meteorological data measurements and data reliability which include maximum and minimum temperature, relative humidity, dew point temperature, radiation, heat flux. There were some outliers and missing data from the measurements. In addition, the latent heat flux and sensible heat flux data were not reasonable and evapotranspiration data did not match at some points. The accuracy and consistency of data stored in a database for the study were secured from the data integrity. Users need to take caution when using meteorological data from the Yongdam catchment in the preparation of water resources planning, environmental impact assessment, and natural hazards analysis.

• Journal of Environmental Impact Assessment
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• v.2 no.2
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• pp.73-83
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• 1993

Increasing concern for the environment in Korea has led to the demand that major policies and large-scale development projects be subjected to detailed impact assessment. This paper reports on the state of data related to the prediction of the environmental impact (EIA) to emphasize the importance of data quality. Environmental impact statements (EIS) consulted with the Ministry of Environment of Korea were analyzed from 1981 through 1992. Many of assessors used existing data and collected supplementary data from field survey. Most of the results of EIA are presented directly or summarized on maps and as graphics. For the national purpose, large source of quality-controlled data such as atmospheric data have been developed, However, there are the deficiency in data to analyze the impact of human activity, and data gaps and incompatibilities among systems. Consequently, the development of data bank systems including computer database and remotely-sensed satellite data is required to improve the quality of data which are relevant to EIA. The data bank system should be organized meaningfully in minimum time with a least cost, and measurement standards must be made explicit. Geographical information systems (GIS) are applicable to the graphic presentation or to the impact prediction model.