• Atmosphere
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• v.18 no.1
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• pp.1-14
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• 2008

The cloud amount, one of the basic parameter in atmospheric observation, have been observed by naked eyes of observers, which is affected by the subjective view. In order to ensure reliable and objective observation, a new algorithm to retrieve cloud amount was constructed using true color images composed of red, green and blue (RGB). The true color image is obtained by the Skyview, an all-sky imager taking pictures of sky, at the Science Building of Yonsei University, Seoul for a year in 2006. The principle of distinguishing clear sky from cloudy sky lies in the fact that the spectral characteristics of light scattering is different for air molecules and cloud. The result of Skyview's algorithm showed about 77% agreement between the observed cloud amount and the calculated, for the error range, the difference between calculated and observed cloudiness, within ${\pm}2$. Seasonally, the best accuracy of about 83% was obtained within ${\pm}2$ range in summer when the cloud amounts are higher, thus better signal-to-noise ratio. Furthermore, as the sky turbidity increased, the error also increased because of increased scattering which can explain the large error in spring. The algorithm still need to be improved in classifying sky condition more systematically with other complimentary instruments to discriminate thin cloud from haze to reduce errors in detecting clouds.

• Journal of Environmental Science International
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• v.23 no.12
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• pp.2121-2127
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• 2014

Analyzing the observational data of volcanic activities around the northern part of Korean peninsula, the odds of volcano eruption increases continuously. For example, the cumulative seismic moment and frequence observed near Mt. Baekdu show a sudden increased values. In this study, predicting the diffusion of volcanic ash for two cases were carried out by using interactive realtime simulator, which was developed during last 2 years as a research and development project. The first case is Sakurajima volcano (VEI=3) erupted in August 2013. The second case is assumed as the volcanic eruption at Mt. Baekdu (VEI=7) under landing circumstance of typhoon Maemi (August 2003) in Korean peninsula. The synoptic condition and ash diffusion for the two cases were simulated by WRF(Weather Research and Forecast) model and Lagrangian dispersion model, respectively. Comparing the simulated result of the first case (i.e., Sakurajima volcano) with satellite image, the diffusion pattern show acceptable result. The interactive realtime simulator can be available to support decision making under volcanic disaster around East Asia by predicting several days of ash dispersion within several minutes with ordinary desktop personal computer.

• Atmosphere
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• v.28 no.3
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• pp.317-324
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• 2018

In this study, we review the ground-based whole-sky camera (WSC), which is developed to continuously capture day and night cloud images using the illumination data from a precision Lightmeter with a high temporal resolution. The WSC is combined with a precision Lightmeter developed in IYA (International Year of Astronomy) for analysis of an artificial light pollution at night and a DSLR camera equipped with a fish-eye lens widely applied in observational astronomy. The WSC is designed to adjust the shutter speed and ISO of the equipped camera according to illumination data in order to stably capture cloud images. And Raspberry Pi is applied to control automatically the related process of taking cloud and sky images every minute under various conditions depending on illumination data from Lightmeter for 24 hours. In addition, it is utilized to post-process and store the cloud images and to upload the data to web page in real time. Finally, we check the technical possibility of the method to observe the cloud distribution (cover, type, height) quantitatively and objectively by the optical system, through analysis of the captured cloud images from the developed device.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.645-652
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• 2020

GK2A(GEO-KOMPSAT-2A)satellite has been operating excellently since its launch in Dec 2018. The secondary payload called KSEM (Korean Space Environment Monitor) was equipped into the GK2A satellite along with AMI (Advanced Meteorological Imager) sensor. KSEM is the Korea's first operational geostationary space weather sensor and has been developed collaboratively by KHU (Kyung Hee University) and KARI (Korea Aerospace Research Institute). The interface works between KSEM and GK2A were conducted by KARI. Various interface tests, which aim for evaluating effective functionality of KSEM with the spacecraft, were intensively conducted at KARI facilities. Main tests consisted of mechanical and electrical check-up activities between the KSEM and GK2A. Interface tests of KSEM, which involve pre-launch tests such as ETB and GK2A system level tests, were conducted to evaluate functional and performance of KSEM before the launch. The tests carried out during the GK2A LEOP (Launch and Early Orbit Phase) and IOT (In Orbit Test) period (Dec 2018 ~ June 2019) showed excellent in-orbit performance of KSEM data.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.367-370
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• 2009

한국해양연구원에서는 2009년 발사 예정인 통신해양기상위성(COMS: Communication, Ocean and Meteorological Satellite)의 해색센서인 정지궤도 해양위성(GOCI: Geostationary Ocean Color Imager) 데이터의 수신, 처리, 배포를 위한 해양위성센터(KOSC: Korea Ocean Satellite Center)를 구축하고 있다. 2005년 "해양위성센터 구축사업"의 시작으로, 전파 수신 환경 등의 조건을 고려하여, 안산에 위치한 한국해양연구원 본원으로 해양위성센터의 위치를 최종 확정하여 구축을 진행하고 있다. 2009년 3월 현재 수신시스템(GDAS: GOCI Data Aquisition System), 자료전처리시스템(IMPS: Image Pre-processing System), 자료처리시스템(GDPS: GOCI Data Processing System), 자료관리 시스템(DMS: Data Management System), 통합감시제어시스템(TMC: Total Management & Controlling System), 기관간 자료교환시스템(EDES: External Data Exchange System) 등이 구축 완료되었고, 위성자료 배포시스템(DDS: Data Distribution System)을 구축하고 있다. 고용량 데이터의 원활한 전송을 위한 데이터센터를 비롯하여 사용자관점에서의 시스템 구축을 추진하고 있으며, 위성 발사 후 사용자 등록을 시작할 계획이다.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.729-741
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• 2012

Among the methods of precipitation data acquisition, a rain gauge station has a distinctive advantage of direct measurement of rainfall itself, but multiple stations should be installed in order to obtain areal precipitation data required for hydrological analysis. On the other hand, a rainfall radar may provide areal distribution of rainfall in real time though it is an indirect measurement of radar echoes on rain drops. Rainfall radars have been shown useful especially for forecasting short-term localized torrential storms that may cause catastrophic flash floods. CAPPI (Constant Altitude Plan Position Indicator), which is one of the several types of radar rainfall image data, has been provided on the Internet in real time by Korea Meteorological Administration (KMA). It is one of the most widely available rainfall data in Korea with fairly high level of confidence as it is produced with bias adjustment and quality control procedures by KMA. The objective of this study is to develop an improved way to extract quantitative rainfall data applicable to even very small watersheds from CAPPI using CIVCOM, which is a new image processing method based on a vector-based scheme proposed in this study rather than raster-based schemes proposed by other researchers. This study shows usefulness of CIVCOM through comparison of rainfall data produced by image processing methods including traditional raster-based schemes and a newly proposed vector-based one.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.434-439
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• 2019

Recently, interest in urban temperature change and ground surface temperature change has been increasing due to weather phenomenon due to global warming, heat island phenomenon caused by urbanization in urban areas. In Korea, weather data such as temperature and precipitation have been collected since 1904. In recent years, there are 96 ASOS stations and 494 AWS weather observation stations. However, in the case of terrestrial networks, terrestrial meteorological data except measurement points are predicted through interpolation because they provide point data for each installation point. In this study, to improve the resolution of ground surface temperature measurement, the surface temperature using satellite image was calculated and its applicability was analyzed. For this purpose, the satellite images of Landsat 8 OLI TIRS were obtained for Seoul Metropolitan City by seasons and transformed to surface temperature by applying NASA equation to the thermal bands. The ground measurement data was based on the temperature data measured by AWS. Since the AWS temperature data is station based point data, interpolation is performed by Kriging interpolation method for comparison with Landsat image. As a result of comparing the satellite image base surface temperature with the AWS temperature data, the temperature difference according to the season was calculated as fall, winter, summer, based on the RMSE value, Spring, in order of applicability of Landsat satellite image. The use of that attribute and AWS support starts at $2.11^{\circ}C$ and RMSE ${\pm}3.84^{\circ}C$, which reflects information from the extended NASA.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1295-1305
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• 2021

Satellite-derived ocean color products are required to effectively monitor clear open ocean and coastal water regions for various research fields. For this purpose, accurate correction of atmospheric effect is essential. Currently, the Geostationary Ocean Color Imager (GOCI)-II ground segment uses the reanalysis of meteorological fields such as European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental Prediction (NCEP) to correct gas absorption by water vapor and ozone. In this process, uncertainties may occur due to the low spatiotemporal resolution of the meteorological data. In this study, we develop water vapor absorption correction model for the GK-2 combined GOCI-II atmospheric correction using Advanced Meteorological Imager (AMI) total precipitable water (TPW) information through radiative transfer model simulations. Also, we investigate the impact of the developed model on GOCI products. Overall, the errors with and without water vapor absorption correction in the top-of-atmosphere (TOA) reflectance at 620 nm and 680 nm are only 1.3% and 0.27%, indicating that there is no significant effect by the water vapor absorption model. However, the GK-2A combined water vapor absorption model has the large impacts at the 709 nm channel, as revealing error of 6 to 15% depending on the solar zenith angle and the TPW. We also found more significant impacts of the GK-2 combined water vapor absorption model on Rayleigh-corrected reflectance at all GOCI-II spectral bands. The errors generated from the TOA reflectance is greatly amplified, showing a large error of 1.46~4.98, 7.53~19.53, 0.25~0.64, 14.74~40.5, 8.2~18.56, 5.7~11.9% for from 620 nm to 865 nm, repectively, depending on the SZA. This study emphasizes the water vapor correction model can affect the accuracy and stability of ocean color products, and implies that the accuracy of GOCI-II ocean color products can be improved through fusion with GK-2A/AMI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.6
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• pp.1209-1218
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• 2015

As the drought disasters are increased in the world, the need of study using satellite image data is on the rise. This study is conducted to analyze the drought in the region using satellite image, and to analyze the correlation with the standard precipitation index (SPI) and the actual drought cases. We selected Dongducheon and Taebaek region for domestic major drought (2001, 2008-2009). The correlation with the SPI and the observed water level data was analyzed using the $0.05^{\circ}$ spatial resolution and 8days MODIS DSI (Drought Severity Index). In Dongducheon, 6-months DSI has a correlation of 0.71 with the SPI (30). In Taebaek, the correlation between 6-months DSI and SPI (90) was a 0.40 and showed an average hit ratio of 65.7% in comparing with the observed water level of study area. In summary, this study showed a limited correlation between DSI based on satellite images and meteorological drought index SPI and confirmed the possibility of using DSI for the domestic study.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.330-340
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• 2015

For this study, we developed an algorithm to estimate the total amount of clouds using sky image data from the Skyviewer equipped with CCD camera. Total cloud amount is estimated by removing mask areas of RGB (Red Green Blue) images, classifying images according to frequency distribution of GBR (Green Blue Ratio), and extracting cloud pixels from them by deciding RBR (Red Blue Ratio) threshold. Total cloud amount is also estimated by validity checks after removing sunlight area from those classified cloud pixels. In order to verify the accuracy of the algorithm that estimates total cloud amount, the research analyzed Bias, RMSE, and correlation coefficient compared to records of total cloud amount earned by human observation from the Gangwon Regional Meteorological Administration, which is in the closest vicinity of the observation site. The cases are selected four daily data from 0800 LST to 1700 LST for each season. The results of analysis showed that the Bias in total cloud amount estimated by the Skyviewer was an average of -0.8 tenth, and the RMSE was 1.6 tenths, indicating the difference in total cloud amount within 2 tenths. Also, correlation coefficient was very high, marking an average of over 0.91 in all cases, despite the distance between the two observation sites (about 4 km).