• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.25-37
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• 2024

Global warming-induced drought inflicts significant socio-economic and environmental damage. In Korea, the persistent drought in the southern region since 2022 has severely affected water supplies, agriculture, forests, and ecosystems due to uneven precipitation distribution. To effectively prepare for and mitigate such impacts, it is imperative to develop proactive measures supported by early monitoring systems. In this study, we analyzed the spatiotemporal changes of multiple evapotranspiration-based drought indices, focusing on the flash drought event in the southern region in 2022. The indices included the Evaporative Demand Drought Index (EDDI), Standardized Precipitation Evapotranspiration Index (SPEI) considering precipitation and temperature, and the Evaporative Stress Index (ESI) based on satellite images. The Standardized Precipitation Index (SPI) and SPEI indices utilized temperature and precipitation data from meteorological observation stations, while the ESI index was based on satellite image data provided by the MODIS sensor on the Terra satellite. Additionally, we utilized the Evaporative Demand Drought Index (EDDI) provided by the North Oceanic and Atmospheric Administration (NOAA) as a supplementary index to ESI, enabling us to perform more effective drought monitoring. We compared the degree and extent of drought in the southern region through four drought indices, and analyzed the causes and effects of drought from various perspectives. Findings indicate that the ESI is more sensitive in detecting the timing and scope of drought, aligning closely with observed drought trends.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1565-1576
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• 2023

An atmospheric correction algorithm based on the radiative transfer model is required to obtain remote-sensing reflectance (R_rs) from the Geostationary Ocean Color Imager-II (GOCI-II) observed at the top-of-atmosphere. This R_rs derived from the atmospheric correction is utilized to estimate various marine environmental parameters such as chlorophyll-a concentration, total suspended materials concentration, and absorption of dissolved organic matter. Therefore, an atmospheric correction is a fundamental algorithm as it significantly impacts the reliability of all other color products. However, in clear waters, for example, atmospheric path radiance exceeds more than ten times higher than the water-leaving radiance in the blue wavelengths. This implies atmospheric correction is a highly error-sensitive process with a 1% error in estimating atmospheric radiance in the atmospheric correction process can cause more than 10% errors. Therefore, the quality assessment of R_rs after the atmospheric correction is essential for ensuring reliable ocean environment analysis using ocean color satellite data. In this study, a Quality Assurance (QA) algorithm based on in-situ R_rs data, which has been archived into a database using Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Bio-optical Archive and Storage System (SeaBASS), was applied and modified to consider the different spectral characteristics of GOCI-II. This method is officially employed in the National Oceanic and Atmospheric Administration (NOAA)'s ocean color satellite data processing system. It provides quality analysis scores for R_rs ranging from 0 to 1 and classifies the water types into 23 categories. When the QA algorithm is applied to the initial phase of GOCI-II data with less calibration, it shows the highest frequency at a relatively low score of 0.625. However, when the algorithm is applied to the improved GOCI-II atmospheric correction results with updated calibrations, it shows the highest frequency at a higher score of 0.875 compared to the previous results. The water types analysis using the QA algorithm indicated that parts of the East Sea, South Sea, and the Northwest Pacific Ocean are primarily characterized as relatively clear case-I waters, while the coastal areas of the Yellow Sea and the East China Sea are mainly classified as highly turbid case-II waters. We expect that the QA algorithm will support GOCI-II users in terms of not only statistically identifying R_rs resulted with significant errors but also more reliable calibration with quality assured data. The algorithm will be included in the level-2 flag data provided with GOCI-II atmospheric correction.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.91-97
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• 2009

It is undertaken systematization of results of satellite and ground observation parameters characterizing a current condition and climatic variability of two selected geographical areas. One of them covers territory of Azerbaijan and another covers a wide area of Caspian See region. Average values and mean square deviations of following values are investigated: outgoing long wave radiation during a day and night (in nebulosity and cloudless). absorbed within a day of the stream of a sunlight of the system in "a terrestrial surface-atmosphere". degree of a covering by clouds of the selected areas during a day and at night, ground temperature values of air. pressure and speed of a wind. Monthly average values of corresponding parameters create a basis of suggested investigations. It has been presented features of a time course of investigated parameters for each month and year in the whole due to the continuously observations since 1982-2000. The scientific problem consists that there are no existed models which authentically would be cover the main aspects of a realities specified changes: they are identified by economic activities. growth of the population and other features of development of a human society or internal fluctuations of biogeophysical/climatic system. Possibilities of predictability of biosphere and climate changes depend on available timely supervision. adequacy of construction of appropriate models. understanding of mechanisms of direct and feedback influences in such complicated systems.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.638-643
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• 2002

MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

• Journal of Environmental Impact Assessment
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• v.15 no.6
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• pp.443-452
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• 2006

Today, satellite remote sensing (RS) and geographic information systems (GIS) plays an important role as an advanced science and technology. This study was developed a Line Density Algorithm which was clarify and describe the thermal front by using NOAA SST (sea surface temperature) and GIS spatial analysis for systemic and effective management of fish raising industry and sea environmental pollution by land reclamation program. Before this, a study about a interpolation method was carry out which was very important for estimate the hidden value between a special point. For this study Inverse Distance Weighted interpolation, Spline interpolation, Kriging interpolation methods were choose and SST data from 2001 to 2004 in spring (March, April, May) were analyzed. According to the study Kriging interpolation method was the very adaptive method from a practical point of view and excellent in description and precision then others. Finally, the result of this study will be use for develope the Line Density Index Algorism.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.97-109
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• 2017

Green tides that developed along the coast of China in 2015 were detected and tracked using vegetation indices from GOCI and Landsat images. Green tides first appeared near the Jiangsu Province on May 14 before increasing in size and number and moving northward to the Shandong Peninsula in mid-June. Typhoon Cham-hom passed through the Yellow Sea on July 12, significantly decreasing the algal population. An algae patch moved east toward Korea and on June 18 and July 4, several masses were found between the southwestern shores of Korea and Jeju Island. The floating masses found in Korean waters were concentrated at the boundary of the open sea and the Jindo cold pool, a phenomenon also observed at the boundary of coastal and offshore waters in China. Sea surface temperatures, derived from NOAA SST data, were found to play a role in generation of the green tides.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.165-167
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• 2003

To evaluate the thermal and water stress of vegetation canopy in Southern Qu$\'{e}$bec, leaf water status was evaluated from vegetation indices derived from SPOT VEGETATION images and surface temperature from NOAA AVHRR images. This study was conducted by investigating vegetation conditions for two different periods, from June to August, 1999 and 2000. The vegetation indices were integrated for the evaluating vegetation conditions as a new index, normalized moisture index (NMI). A trapezoid was defined by the NMI and surface temperature, and the thermal and water status of the vegetation canopy was determined according to separate small sections within the trapezoid.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.47-51
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• 2009

증발산량을 산정하는 것은 자연현상과 인문현상을 이해하는 것의 기초가 된다. 이에, 최근 증발산량을 추정하는 많은 연구가 진행되고 있는 가운데 원격탐사 기법을 이용하는 것이 효과적인 것으로 알려지고 있다. 본 연구에서 소개할 SEBAL (Surface Energy Balance Algorithm for Land) (Bastiaanssen, 1995) 모형은 Landsat이나 NOAA 또는 MODIS 같은 원격탐사 위성으로부터 획득한 디지털 이미지 데이터(위성영상)를 이용하여, 지표에서 일어나는 증발산과 기타의 에너지 교환을 계산하는 이미지-프로세싱 모델이다. 우리나라 대상 유역에 위성영상을 사용하여 증발산량을 추정하는 SEBAL 모형의 적용 가능성을 검토하여, 유역 내 증발산량 분포의 시공간적 특성을 분석하고자 하였다. 연구 대상 지역은 유역 면적 약 6661.1km2의 충주댐 유역으로, Terra MODIS 위성영상을 이용하였다. SEBAL 증발산량의 평가를 위해 Penman-Monteith 공식에 의해 계산된 증발산량을 이용하여 비교하였으며, 그 결과 오차가 허용 가능한 10% 이내로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2184-2189
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• 2009

China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.13-18
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• 1999

Land cover map of 30 arc-second grid by NOAA AVHRR data for the whole Asia was produced by the authors as the project of the Asian Association on Remote Sensing(AARS). Land cover change monitoring of continental scale by satellite data needs preprocessing to remove undesirable factors due to noises, atmosphere, or the effect by solar zenith angle. The paper describes the method to remove these factors. The most important thing for better mapping/monitoring in the future is the accumulation of ground truth data by many land cover related researchers. The project of the development of Global Land Cover Ground Truth Database(GLCGT-DB) is proposed.