• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.07a
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• pp.1073-1075
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• 2001

The nitrogen oxides, NO and NO2, abbreviated usually as NOx, emitted from combustion facilities such as power plants and automobiles are the typical air-pollutants causing acid rain and photochemical smog. In order to solve the NOx-related pollution problems effectively, we need efficient techniques to monitor NOx in the combustion exhausts and in environments. Development of solid-state electrochemical devices for detecting NOx is demonstrated based on various combination of solid electrolytes and auxiliary sensing materials. The object of this research is to develop various sensor performance for solid state amperometric sensor, and to test gas sensor performance manufactured. So we try to present a guidance for developing amperometric gas sensor. We concentrated on development of manufacturing process and performance test.

• Proceedings of the KSRS Conference
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• v.2
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• pp.660-663
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• 2006

Rainfall estimation is important to weather forecast, flood control, hydrological plan. The empirical and statistical methods by measured data(surface rain gauge, rainfall radar, Satellite) is commonly used for rainfall estimation. In this study, the rainfall intensity for East Asia region was estimated using the empirical relationship between SSM/I data of DMSP satellite and brightness temperature of GEOS-9(10.7${\mu}m$) with cloud types(ISCCP and MSG classification). And the empirical formula for rainfall estimation was produced by PMM (Probability Matching Method).

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07a
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• pp.222-225
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• 2002

The nitrogen oxides, NO and NO2, abbreviated usually as NOx, emitted from combustion facilities such as power plants and automobiles are the typical air-pollutants causing acid rain and photochemical smog. In order to solve the NOx-related pollution problems effectively, we need efficient techniques to monitor NOx in the combustion exhausts and in environments. Development of solid-state electrochemical devices for detecting NOx is demonstrated based on various combination of solid electrolytes and auxiliary sensing materials. The object of this research is to develop various sensor performance for solid state amperometric sensor, and to test gas sensor performance manufactured. So we try to present a guidance for developing amperometric gas sensor.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.365-368
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• 2007

Millimeter-wave (MMW) imaging radiometer systems have an attractive advantage to obtain an image through low visibility weather conditions such as fog, clouds and light rain compared with visible and infrared imaging systems. Many countries have developed a various kinds of MMW imaging radiometers for the aim of low cost and high performance. In Korea, Millimeter-wave Imaging RAdiometer Equipment (MIRAE) has been developed since the end of 2006. Recently the development of some modules was finished for the test model. This paper describes the design and development of the MIRAE. In addition, the test results of its manufactured modules are presented.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.924-926
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• 2000

The nitrogen oxides, NO and NO2, abbreviated usually as NOx, emitted from combustion facilities such as power plants and automobiles are the topical air-pollutants causing acid rain and photochemical smog. In order to solve the NOx-related pollution problems effectively, we need efficient techniques to monitor NOx in the combustion exhausts and in environments. Development of solid-state electrochemical devices for detecting NOx is demonstrated based on various combination of solid electrolytes and auxiliary sensing materials. The object of this research is to develop various sensor performance for solid state amperometric sensor, and to test gas sensor performance manufactured. So we try to present a guidance for developing amperometric gas sensor. We concentrated on development of manufacturing process and performance test.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.528-530
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• 2003

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM ? TMI and Precipitation Radar (PR) respectively during a typhoon even named ? RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall fnus estimated using PST and SI shows some Underestimation as compared to the 2A25 rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.70-82
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• 2020

Recently, a lot of damages have been caused by urban flooding, and heavy rainfall that temporarily occur are the main causes of these phenomenons. The damages caused by urban flooding are identified as the change in the water balance in urban areas. To indirectly identify it, this research analyzed the change in the remote sensing indices on each land cover before and after heavy rainfall by utilizing daily precipitation data and multi-temporal Sentinel-2 satellite imagery. Cases of heavy rain advisory and warning were selected based on the daily precipitation data. And statistical fluctuation were compared by acquiring Sentinel-2 satellite images during the corresponding period and producing them as NDVI, NDWI and NDMI images about each land cover with a radius of 1,000 m based on the Seoul Weather Station. As a result of analyzing the maximum value, minimum value, mean and fluctuation of the pixels that were calculated in each remote sensing index image, there was no significant changes in the remote sensing indices in urban areas before and after heavy rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.168-168
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• 2023

The frequent occurrence of cyanobacterial harmful algal blooms (CHABs) in inland waters under climate change seriously damages the ecosystem and human health and is becoming a big problem in South Korea. Satellite remote sensing is suggested for effective monitoring CHABs at a larger scale of water bodies since the traditional method based on sparse in-situ networks is limited in space. However, utilizing a standalone variable of satellite reflectances in common CHABs dual-models, which relies on both chlorophyll-a (Chl-a) and phycocyanin or cyanobacteria cells (Cyano-cell), is not fully beneficial because their seasonal variation is highly impacted by surrounding meteorological and bio-environmental factors. Along with the development of Artificial Intelligence (AI), monitoring CHABs from space with analyzing the effects of environmental factors is accessible. This study aimed to investigate the potential application of AI in the dual-model strategy (Chl-a and Cyano-cell are output parameters) for monitoring seasonal dynamics of CHABs from satellites over Korean inland waters. The Sentinel-3 satellite was selected in this study due to the variety of spectral bands and its unique band (620 nm), which is sensitive to cyanobacteria. Via the AI-based feature selection, we analyzed the relationships between two output parameters and major parameters (satellite water-leaving reflectances at different spectral bands), together with auxiliary (meteorological and bio-environmental) parameters, to select the most important ones. Several AI models were then employed for modelling Chl-a and Cyano-cell concentration from those selected important parameters. Performance evaluation of the AI models and their comparison to traditional semi-analytical models were conducted to demonstrate whether AI models (using water-leaving reflectances and environmental variables) outperform traditional models (using water-leaving reflectances only) and which AI models are superior for monitoring CHABs from Sentinel-3 satellite over a Korean inland water body.

• Korean Journal of Remote Sensing
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• v.36 no.5_1
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• pp.749-762
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• 2020

Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.773-786
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• 2017

This study was to analyze data of climate change impacts on social infrastructure using text-mining methodology, and to visualize the spatial information by integrating those with regional data layers. First of all, the study identified that the following social infrastructure; power, oil and resource management, transport and urban, environment, and water supply infrastructures, were affected by five kinds of climate factors (heat wave, cold wave, heavy rain, heavy snow, strong wind). Climate change impacts on social infrastructure were then analyzed and visualized by regions. The analysis resulted that transport and urban infrastructures among all kinds of infrastructure were highly impacted by climate change, and the most severe factors of the climate impacts on social infrastructure were heavy rain and heavy snow. In addition, it found out that social infrastructure located in Seoul and Gangwon-do region were relatively largely affected by climate change. This study has significance that atypical data in media was used to analyze climate change impacts on social infrastructure and the results were translated into spatial information data to analyze and visualize the climate change impacts by regions.