• Journal of the Korean earth science society
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• v.43 no.5
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• pp.591-603
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• 2022

The color and optical properties of seawater are determined by the interaction between dissolved organic and inorganic substances and plankton contained in it. The Ieodo - Ocean Research Institute (I-ORS), located in the East China Sea, is affected by the low salinity of the Yangtze River in the west and the Tsushima Warm Current in the south. Thus, it is a suitable site for analyzing the fluctuations in circulation and optical properties around the Korean Peninsula. In this study, seawater surrounding the I-ORS was classified according to its optical characteristics using the satellite remote reflectance observed with Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua and National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) from January 2016 to December 2020. Additionally, the variation characteristics of optical water types (OWTs) from different seasons were presented. A total of 59,532 satellite match-up data (d ≤ 10 km) collected from seawater surrounding the I-ORS were classified into 23 types using the spectral angle mapper. The OWTs appearing in relatively clear waters surrounding the I-ORS were observed to be greater than 50% of the total. The maximum OWTs frequency in summer and winter was opposite according to season. In particular, the OWTs corresponding to optically clear seawater were primarily present in the summer. However, the same OWTs were lower than overall 1% rate in winter. Considering the OWTs fluctuations in the East China Sea, the I-ORS is inferred to be located in the transition zone of seawater. This study contributes in understanding the optical characteristics of seawater and improving the accuracy of satellite ocean color variables.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1255-1272
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• 2023

Satellite-based chlorophyll-a concentration, produced as a long-term time series, is crucial for global climate change research. The production of data without gaps through the merging of time-synthesized or multi-satellite data is essential. However, studies related to satellite-based chlorophyll-a concentration in the waters around the Korean Peninsula have mainly focused on evaluating seasonal characteristics or proposing algorithms suitable for research areas using a single ocean color sensor. In this study, a merging dataset of remote sensing reflectance from the geostationary sensor GOCI-II and polar-orbiting sensors (MODIS, VIIRS, OLCI) was utilized to achieve high spatial coverage of chlorophyll-a concentration in the waters around the Korean Peninsula. The spatial coverage in the results of this study increased by approximately 30% compared to polar-orbiting sensor data, effectively compensating for gaps caused by clouds. Additionally, we aimed to quantitatively assess accuracy through comparison with global chlorophyll-a composite data provided by Ocean Colour Climate Change Initiative (OC-CCI) and GlobColour, along with in-situ observation data. However, due to the limited number of in-situ observation data, we could not provide statistically significant results. Nevertheless, we observed a tendency for underestimation compared to global data. Furthermore, for the evaluation of practical applications in response to marine disasters such as red tides, we qualitatively compared our results with a case of a red tide in the East Sea in 2013. The results showed similarities to OC-CCI rather than standalone geostationary sensor results. Through this study, we plan to use the generated data for future research in artificial intelligence models for prediction and anomaly utilization. It is anticipated that the results will be beneficial for monitoring chlorophyll-a events in the coastal waters around Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.985-996
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• 2000

In the coastal zone, to draw up short and medium range weather forecasts, mesoscale pluviogenic systems coming from the sea have to be observed in real time. These observations use remote sensing. However, satellite remote sensing is not sufficient to describe pluviogenic systems; reference to radar long distance observations is indispensable. This paper deals with the corrections, which must be made to long distance radar data if the rainfall field is to be both accurately and quantitatively defined. The error due to vertical variation in the reflectivity factor can be corrected from estimation of the mean profiles or by a climatic adjustment method. Atten-uation in the propagation can be corrected by an iterative polarimetric method. These various correc-tions permit the distance validity limits of radar data to be extended.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.605-608
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• 2009

It is necessary to estimate the Doppler spectrum for each range cell for the extraction of useful information from the return echoes in radar systems used for the remote sending purpose. However, The conventional spectrum estimation method, FFT(Fast Fourier Transform), called the Doppler filter bank, causes the frequency resolution problem if the dwell time is relatively short. This short acquisition time also spreads the side lobe levels of return echoes further, resulting in difficulties for the discrimination of weak target signals included in relatively strong target echoes. Therefore, in this paper, the efficient Doppler spectrum estimation methods are compared and investigated through the parameter spectrum estimation in the time domain to overcome these problems.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.110-110
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• 2021

사회적, 환경적으로 크고 작은 문제를 일으키는 녹조현상은 수생태계에서 1차 생산자로 없어서는 안 될 조류의 과대 성장으로 인해 주로 나타난다. 담수조류는 크게 녹조류, 남조류, 규조류 3종으로 나누어지며, 특히 남조류는 계절별 천이에 따른 발생 시 과대 성장하는 특성으로 인해 녹조현상에 가장 큰 원인이 된다. 이러한 녹조현상의 원인에 따라 환경부에서는 발령기준 항목을 chl-a와 남조류 세포수에서 2016년 이후 남조류 세포수 만으로 발령기준 항목을 개정하였다. 따라서, 녹조현상에 대한 신속한 대처를 위해서는 남조류에 대한 분포에 대해 파악하는 것이 가장 우선시 되며 이를 위해 신속한 모니터링을 필요로 한다. 하지만 현재 조류 모니터링을 위해서는 직접 채수를 통한 검경 또는 Lisst, YSI와 같은 직접 계측 센서를 활용하여 모니터링을 진행을 하고 있으며 이러한 점, 선 단위의 측정은 전반적인 조류 분포 및 현황에 대하여 파악과 신속한 모니터링에 한계가 있다. 이러한 한계에 대안으로 위성영상, 다중분광 및 초분광 영상을 활용한 면단 위의 원격 모니터링을 통해 신속하고 하천 내 전반적인 조류 농도 분석을 위한 연구가 다양하게 진행되고 있다. 본 연구에서는 UAV를 활용한 초분광센서를 이용하여 하천과 일정한 반사율을 가지는 반사천을 촬영하고 취득한 초분광영상 보정 및 분석을 진행하였다. 최적 밴드 비를 산정하고 YSI를 통한 Chl-a 결과를 이용하여 분광 특성별 맵핑을 통한 공간적 분포의 조류 농도를 산정하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.48-48
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• 2020

최근 이상기후변화로 인해 수환경 변화가 일어나고 있다. 그로 인해 국내에서 조류의 과대성장이 빈번히 발생되고 있으다. 이로 인해 유해남조류 등 조류가 생산하는 독성물질, 이취미 물질은 수질을 악화시키고 있으며, 생태계에 큰영향을 미친다. 조류는 하천에서 넓은 분포로 발생하게 되는데 이러한 조류 모니터링에는 많은 인력과 시간이 소요된다. 국내에선 인력과 시간을 줄이기 위해 최근 원격탐사 기법을 이용한 조류 모니터링에 대한 연구가 많이 진행되고 있다. 본 연구에서는 녹조류, 남조류 5종을 이용해 실험을 진행하였다. 사용된 초분광 센서는 CORNING사의 microHSI^TM 410 SHARK를 이용하였으며 파장 400-1000 nm에서 NIR(visNIR)파장을 분석할 수 있으며, 초분광 센서를 정사로 영상을 촬영하기 위해 짐벌을 이용하여 영상을 수집하였다. 영상을 촬영 전 방사보정을 하기 위해 시료와 동일 선상에 99% 반사율을 갖는 백색반사판을 같이 촬영하여 방사보정을 진행하였다. 본 연구에서는 시기와 상관없이 조류에 대한 연구를 하기위해 조류배양액을 이용하였으며, 남조의 경우 470 nm에서 분광 특성을 나타내었으며, 녹조의 경우 477-510 nm에서 분광 특성을 나타났다. 초분광영상을 통해 기초라이브러리를 구축하고 구축된 라이브러리를 통해 조류의 분광특성을 분석하고 제시하여 하천에 적용하고자 한다.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.507-519
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• 2017

The applications of NDVI (Normalized Difference Vegetation Index) as a vegetation index has been widely used to understand vegetation biomass and physiological activities. However, NDVI is not suitable way for monitoring vegetation stress because it is less sensitive to change in physiological state than biomass. PRI (Photochemical Reflectance Index) is well developed to present physiological activities of vegetation, particularly high-light-stress condition, and it has been adopted in several satellites to be launched in the future. Thus, the understanding of PRI performance and the development of analysis method will be necessary. This study aims to interpret the characteristics of light-stress-sensitive PRI in shadow areas and to evaluate the PRI calculated by other wavelengths (i.e., 488.9 nm, 553.6 nm, 646.9 nm, and 668.4 nm) instead of 570 nm that used in original PRI. Using airborne-based hyperspectral image, we found that PRI values were increased in shadow detection due to the reduction of high light induced physiological stress. However, the qualities of both PRI and NDVI data were dramatically decreased when the shadow index (SI) exceeded the threshold (SI<25). In addition, the PRI calculated using by 553.6 nm had best correlation with original PRI. This relationship was improved by multiple regression analysis including reflectances of RED and NIR. These results will be helpful to the understanding of physiological meaning on the application of PRI.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.599-605
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• 2017

Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.101-116
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• 1995

The fact that the demands on traffic data collection are imposed by economic and safety considerations raisese the question of the potential for complementing existing traffic data collection programs with satellite data. Evaluating and monitoring traffic characteristics is becoming increasingly important as worsening congestion, declining economic situations, and increasing environmental sensitivies are forcing the government and municipalities to make better use of existing roadway capacities. The present system of using automatic counters at selected points on highways works well from a temporal point of view (i.e., during a specific period of time at one location). However, the present system does not cover the spatial aspects of the entire road system (i.e., for every location during specific periods of time); the counters are employed only at points and only on selected highways. This lack of spatial coverage is due, in part, to the cost of the automatic counters systems (fixed procurement and maintenance costs) and of the personal required to deploy them. The current procedure is believed to work fairly well in the aggregate mode, at the macro level. However, at micro level, the numbers are more suspect. In addition, the statistics only work when assuming a certain homogenity among characteristics of highways in the same class, an assumption that is impossible to test whn little or no data is gathered on many of the highways for a given class. In this paper, a remote sensing system as complement of the existing system is considered and implemented. Since satellite imagery with high resolution is not available, digitized panchromatic imagery acquired from an aircraft platform is utilized for initial test of the feasibility and performance capability of remote sensing data. Different levels of imagery resolutions are evaluated in an attempt to determine what vehicle types could be classified and counted against a background of pavement types, which might be expected in panchromatic satellite imagery. The results of a systematic study with three different levels of resolutions (1m, 2m and 4m) show that the panchromat ic reflectances of vehicles and pavements would be distributed so similarly that it would be difficult to classify systematically and analytically remotely sensing vehicles on pavement within panchromatic range. Anaysis of the aerial photographs show that the shadows of the vehicles could be a cue for vehicle detection.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.537-546
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• 2007

In hyperspectral remote sensing, linear spectral mixture model is a common procedure decomposing into the components of a mixed pixel and estimating the fraction of each end-member. Although linear spectral mixture model is frequently used in geology and mineral mapping because this model is simple and easy to apply, this model is not always valid in forest and urban area having rather complex structure. This study aims to analyze possible error for applying linear spectral mixture model. For the study, we measured laboratory spectra of mixture sample, having various materials, fractions, distributions. The accuracy of linear mixture model is low with the mixture sample having similar fraction because the multi-scattering between components is maximum. Additionally, this multi-scattering is related to the types, fraction, and distribution of components. Further analysis is necessary to quantify errors from linear spectral mixture model.