• Proceedings of the Korean Environmental Health Society Conference
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• 2003.06a
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• pp.196-198
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• 2003

A prospect of environmental health information system was proposed for managing residents health of industrial complex area, which might imply the health effects by environmental pollution. From reviewing other environmental or health information system and making case database for past research, the direction and approach plans suggested construction of database and its structure for surveillance of health effects from an environmental pollution by environmental epidemiology in Korea. Results showed future requirement for developed algorithm which supports decision maker in environmental health policy and administration process.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.161-167
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• 2021

This paper presents the method to quantitatively evaluate the uncertainty of the semi-empirical Bidirectional Reflectance Distribution Function (BRDF) model for Himawari-8/AHI. The uncertainty of BRDF modeling was affected by various issues such as assumption of model and number of observations, thus, it is difficult that evaluating the performance of BRDF modeling using simple uncertainty equations. Therefore, in this paper, Monte-Carlo method, which is most dependable method to analyze dynamic complex systems through iterative simulation, was used. The 1,000 input datasets for analyzing the uncertainty of BRDF modeling were generated using the Second Simulation of a Satellite Signal in the Solar Spectrum (6S) Radiative Transfer Model (RTM) simulation with MODerate Resolution Imaging Spectroradiometer (MODIS) BRDF product. Then, we randomly selected data according to the number of observations from 4 to 35 in the input dataset and performed BRDF modeling using them. Finally, the uncertainty was calculated by comparing reproduced surface reflectance through the BRDF model and simulated surface reflectance using 6S RTM and expressed as bias and root-mean-square-error (RMSE). The bias was negative for all observations and channels, but was very small within 0.01. RMSE showed a tendency to decrease as the number of observations increased, and showed a stable value within 0.05 in all channels. In addition, our results show that when the viewing zenith angle is 40° or more, the RMSE tends to increase slightly. This information can be utilized in the uncertainty analysis of subsequently retrieved geophysical variables.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.181-187
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• 2003

For the moving objects with environmental sensors such as object tracking moving robot with audio and video sensors, environmental information acquired from sensors keep changing according to movements of objects. In such case, due to lack of adaptability and system complexity, conventional control schemes show limitations on control performance, and therefore, sensory-motor systems, which can intuitively respond to various types of environmental information, are desirable. And also, to improve the system robustness, it is desirable to fuse more than two types of sensory information simultaneously. In this paper, based on Braitenberg's model, we propose a sensory-motor based fusion system, which can trace the moving objects adaptively to environmental changes. With the nature of direct connecting structure, sensory-motor based fusion system can control each motor simultaneously, and the neural networks are used to fuse information from various types of sensors. And also, even if the system receives noisy information from one sensor, the system still robustly works with information from other sensors which compensates the noisy information through sensor fusion. In order to examine the performance, sensory-motor based fusion model is applied to object-tracking four-foot robot equipped with audio and video sensors. The experimental results show that the sensory-motor based fusion system can tract moving objects robustly with simpler control mechanism than model-based control approaches.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.3 s.21
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• pp.123-130
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• 2002

This study is aimed to build an effective information management system for natural ecosystem in local Kang-wha area. We analyze the management strategies for the information related to environment ecosystem and natural ecosystem. A prototype is applied to equip search functions for related-agency information, natural environmental information, spatial information, and ecosystem information. It is also capable of editing the information for related-agency information and natural environmental information. Developed various for future study, a prototype of natural eco-information management system will be operated, which discovers and selves potential problems. It is, in turn, utilited for environmental management system of water quality, air quality and waste management. As the final goal, it is expected to build a total environment information management system by integrating those different environmental information systems.

• Journal of Environmental Impact Assessment
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• v.12 no.1
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• pp.23-34
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• 2003

The emergency response modeling system CARIS has been developed at CCSM (Center for Chemical Safety Management), NIER (National Institute of Environmental Research) to track and predict dispersion of hazardous chemicals for the environmental decision support in case of accidents at chemical or petroleum companies in Korea. The main objective of CARIS is to support making decision by rapidly providing the key information on the efficient emergency response of hazardous chemical accidents for effective approaches to risk management. In particular, the integrated modeling system in CARIS consisting of a real-time numerical weather forecasting model and air pollution dispersion model is supplemented for the diffusion forecasts of hazardous chemicals, covering a wide range of scales and applications for atmospheric information. In this paper, we introduced the overview of components of CARIS and described the operational modeling system and its configurations of coupling/integration in CARIS. Some examples of the operational modeling system is presented and discussed for the real-time risk assessments of hazardous chemicals.

• Spatial Information Research
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• v.7 no.1
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• pp.13-27
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• 1999

This is a pilot study to develop an environmental information system, that is a compute. system for managing various urban environments data of S.M.C(Seoul Metropolitar City), and is also supporting the environmental policy decision-making for the city government. With 2 times of business analysis, the present status of environmental information management in S.M.C. and the major business processes and the data required to computerization were produced. As a result of this study, the model of S.E.I.S.(Seoul Environmental Information System) was developed, which includes the purpose of system, basic system components, and functions of subsystems. Finally a comprehensive strategy for developing the S.E.I.S which includes action plans and annual plans, organizaions for operation, and for project management was provided.

• Journal of Environmental Science International
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• v.18 no.8
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• pp.899-910
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• 2009

We classified wind sectors according to the wind features in South Korea. In order to get the information of wind speed and wind direction, we used and improved on the atmospheric numerical model. We made use of detailed topographical data such as terrain height data of an interval of 3 seconds and landuse data produced at ministry of environment, Republic of Korea. The result of simulated wind field was improved. We carried out the cluster analysis to classify the wind sectors using the K-means clustering. South Korea was classified as 8 wind sectors to the annual wind field.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.85-95
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• 2021

Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.777-788
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• 2021

Since aerosol has a relatively short duration and significant spatial variation, satellite observations become more important for the spatially and temporally continuous quantification of aerosol. However, optical remote sensing has the disadvantage that it cannot detect AOD (Aerosol Optical Depth) for the regions covered by clouds or the regions with extremely high concentrations. Such missing values can increase the data uncertainty in the analyses of the Earth's environment. This paper presents a spatial gap-filling framework using a univariate statistical method such as DCT-PLS (Discrete Cosine Transform-based Penalized Least Square Regression) and FMM (Fast Matching Method) inpainting. We conducted a feasibility test for the hourly AOD product from AHI (Advanced Himawari Imager) between January 1 and December 31, 2019, and compared the accuracy statistics of the two spatial gap-filling methods. When the null-pixel area is not very large (null-pixel ratio < 0.6), the validation statistics of DCT-PLS and FMM techniques showed high accuracy of CC=0.988 (MAE=0.020) and CC=0.980 (MAE=0.028), respectively. Together with the AI-based gap-filling method using extra explanatory variables, the DCT-PLS and FMM techniques can be tested for the low-resolution images from the AMI (Advanced Meteorological Imager) of GK2A (Geostationary Korea Multi-purpose Satellite 2A), GEMS (Geostationary Environment Monitoring Spectrometer) and GOCI2 (Geostationary Ocean Color Imager) of GK2B (Geostationary Korea Multi-purpose Satellite 2B) and the high-resolution images from the CAS500 (Compact Advanced Satellite) series soon.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.497-500
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• 2005

Research and development of remote sensing technique is necessary so that more accurate and extensive information may be obtained. To achieve this goal, the synthesized technique which integrates the high resolution optic and SAR image, and topographical information was examined to investigate the quantitative/qualitative characteristics of the Earth's surface environment. For this purpose, high-precision DEMs of Jeju-Island was generated and data fusion algorithm was developed in order to integrate the multi-spectral optic and polarimetric SAR image. Three dimensional land-cover and two dimensional soil moisture maps were generated conclusively so as to investigate the Earth's surface environments and extract the geophysical parameters.