• Journal of the Korean earth science society
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• v.41 no.6
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• pp.617-629
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• 2020

Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.176-192
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• 2006

The need for a systematic drought management has increased since last countrywide drought in 2001. Naturally various studies for establishing drought plan and preventing drought disaster have been conducted. MODIS image provided by Terra satellite has effective spatial and temporal resolutions to observe spatial and temporal characteristics of a region. MODIS data products are easy for preprocessing and correcting geometrically and provide various data set in regular which are applicable for drought monitoring. In this study, Ansung river and the upstream of South Han river basin was chosen for case study to identify and assess spring drought. The multi-period MODIS image and accumulated precipitation were used to detect not only the drought year but also the vegetation change of normal year and the result were compared with various spatial data. The result shows NDVI and LSWI with is more appropriate than LST for assesing spring drought in Korea and two month cumulative precipitation has moderate relationship with drought. It is necessary to use MODIS image which has same period and same space for effective drought analysis because drought is also affected by landover and altitude.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.337-347
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• 2016

Carbon dioxide ($CO_2$) and methane ($CH_4$) were measured in a rice-barley double cropping and rice mono cropping paddy fields, which are located in the southwestern coast of Korea, over a one-year period. Net ecosystems $CO_2$ exchange (NEE) and ecosystem respiration (Re) were estimated by the eddy covariance (EC) method, and an automatic open/close chamber (AOCC) method was used to measure $CH_4$ fluxes. Environmental factors (solar radiation, air temperature, precipitation etc.) were also measured along with fluxes. After the quality control and gap-filling, the observed fluxes were analyzed. As a result, NEE was -603.0 and $-471.5g\;C\;m^{-2}\;yr^{-1}$ in rice-barley double cropping and rice mono cropping paddy field, respectively. $CH_4$ emissions increased during the course of flooded days and were similar in two cropping paddy field. Accoding to rough results considering only fluxes of $CO_2$ and $CH_4$, it was estimated that the carbon absorbation in rice-barley double cropping paddy field was higher than that in rice mono cropping paddy field by $128.9g\;C\;m^{-2}\;yr^{-1}$.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1219-1230
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• 2022

Multi-spectral drones in agricultural observation require quantitative and reliable data based on physical quantities such as radiance or reflectance in crop yield analysis. In the case of remote sensing data for crop monitoring, images taken in the same area over time-series are required. In particular, biophysical data such as leaf area index or chlorophyll are analyzed through time-series data under the same reference, it can be directly analyzed. So, comparable reflectance data are required. Orthoimagery using drone images, the entire image pixel values are distorted or there is a difference in pixel values at the junction boundary, which limits accurate physical quantity estimation. In this study, reflectance and vegetation index based on drone images were calculated according to the correction method of drone images for time-series crop monitoring. comparing the drone reflectance and ground measured data for spectral characteristics analysis.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.88-88
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• 2021

최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

• Journal of the Korean Geophysical Society
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• v.2 no.1
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• pp.39-44
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• 1999

High-resolution images are drawn from existing seismic data which were originally obtained by Korea Ocean Research & Development Institute (KORDI) during 1994-1997 for deep seismic studies on the East Sea of Korea. These images are analyzed for mapping Quaternary faults and near-bottom gas pockets. First 12 channels are selected from shot gathers for reprocessing. The processing sequence adopted for high-resolution seismic images comprises data copy, trace editing, true amplitude recovery, common-midpoint sorting, initial muting, prestack deconvolution, bandpass filtering, stacking, highpass filtering, poststack deconvolution, f-x migration, and automatic gain control (AGC). Among these processing steps, predictive deconvolution, highpass filtering, and short window AGC are the most significant in enhancement of resolution. More than 200 Quaternanry faults are interpreted on the migrated sections in the shallow depths beneath the seafloor. Although numerous faults are found mostly at the western continental slope and boundaries of the Ulleung Basin, significant amount of the faults are also indicated within the basin. Many of these faults are believed to be formed with reactivation of basement, from geotectonic activities including volcanism, and often originated in Tertiary, indicating that the tectonic regime of the East Sea might be unstable. Existence of shallow gas pockets casts real hazardous warnings to deep-sea drillings and/or to underwater constructions such as inter-island cables and gas pipelines. On the other hand, discovery of these gas pockets heightens the interests in developing natural resources in the East Sea. Reprocessed seismic sections, however, show no typical seismic characteristics for gas hydrates such as bottom-simulating reflectors in the western continental slope and ocean floor.

• Korean Journal of Remote Sensing
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• v.37 no.5_2
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• pp.1281-1293
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• 2021

The recent launch of the GOCI-II enables South Korea to have the world's first capability in deriving the ocean color data at geostationary satellite orbit for about 20 years. It is necessary to develop a consistent long-term ocean color time-series spanning GOCI to GOCI-II mission and improve the accuracy through validation using in situ data. To assess the GOCI-II's early mission performance, the objective of this study is to compare the GOCI-II Chlorophyll-a concentration (Chl-a), Colored Dissolved Organic Matter (CDOM), and remote sensing reflectances (R_rs) through comparison with the GOCI data. Overall, the distribution of GOCI-II Chl-a corresponds with that of the GOCI over the Yellow Sea, Korea Strait, and the Ulleung Basin. In particular, a smaller RMSE value (0.07) between GOCI and GOCI-II over the summer Ulleung Basin confirms the GOCI-II data's reliability. However, despite the excellent correlation, the GOCI-II tends to overestimate Chl-a than the GOCI over the Yellow Sea and Korea Strait. The similar over-estimation bias of the GOCI-II is also notable in CDOM. Whereas no significant bias or error is found for R_rs at 490 nm and 550 nm (RMSE~0), the underestimation of R_rs at 443 nm contributes to the overestimation of GOCI-II Chl-a and CDOM over the Yellow Sea and the Korea Strait. Also, we show over-estimation of GOCI-II R_rs at 660 nm relative to GOCI to cause a possible bias in Total suspended sediment. In conclusion, this study confirms the initial reliability of the GOCI-II ocean color products, and upcoming update of GOCI-II radiometric calibration will lessen the inconsistency between GOCI and GOCI-II ocean color products.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.637-654
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• 2023

In recent years, the number of users has been increasing with the rapid development of earth observation satellites. In response, the Committee on Earth Observation Satellites (CEOS) has been striving to provide user-friendly satellite images by introducing the concept of Analysis Ready Data (ARD) and defining its requirements as CEOS ARD for Land (CARD4L). In ARD, a mask called an Unusable Data Mask (UDM), identifying unnecessary pixels for land analysis, should be provided with a satellite image. UDMs include clouds, cloud shadows, terrain shadows, etc. Terrain shadows are generated in mountainous terrain with large terrain relief, and these areas cause errors in analysis due to their low radiation intensity. previous research on terrain shadow detection focused on detecting terrain shadow pixels to correct terrain shadows. However, this should be replaced by the terrain correction method. Therefore, there is a need to expand the purpose of terrain shadow detection. In this study, to utilize CAS500-4 for forest and agriculture analysis, we extended the scope of the terrain shadow detection to shaded areas. This paper aims to analyze the potential for terrain shadow detection to make a terrain shadow mask for South and North Korea. To detect terrain shadows, we used a Hill-shade algorithm that utilizes the position of the sun and a surface's derivatives, such as slope and aspect. Using RapidEye images with a spatial resolution of 5 meters and Sentinel-2 images with a spatial resolution of 10 meters over the Korean Peninsula, the optimal threshold for shadow determination was confirmed by comparing them with the ground truth. The optimal threshold was used to perform terrain shadow detection, and the results were analyzed. As a qualitative result, it was confirmed that the shape was similar to the ground truth as a whole. In addition, it was confirmed that most of the F1 scores were between 0.8 and 0.94 for all images tested. Based on the results of this study, it was confirmed that automatic terrain shadow detection was well performed throughout the Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.455-464
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• 2014

After launching the Geostationary Ocean Color Imager (GOCI) on June 2010, field campaigns were performed routinely around Korean peninsula to collect in-situ data for calibration and validation. Key measurements in the campaigns are radiometric ones with field radiometers such as Analytical Spectral Devices FieldSpec3 or TriOS RAMSES. The field radiometers must be regularly calibrated. We, in the paper, introduce the optical laboratory built in KOSC and the relative calibration method for in-situ measurement spectroradiometer. The laboratory is equipped with a 20-inch integrating sphere (USS-2000S, LabSphere) in 98% uniformity, a reference spectrometer (MCPD9800, Photal) covering wavelengths from 360 nm to 1100 nm with 1.6 nm spectral resolution, and an optical table ($3600{\times}1500{\times}800mm^3$) having a flatness of ${\pm}0.1mm$. Under constant temperature and humidity maintainance in the room, the reference spectrometer and the in-situ measurement instrument are checked with the same light source in the same distance. From the test of FieldSpec3, we figured out a slight difference among in-situ instruments in blue band range, and also confirmed the sensor spectral performance was changed about 4.41% during 1 year. These results show that the regular calibrations are needed to maintain the field measurement accuracy and thus GOCI data reliability.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1181-1191
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• 2013

This study have implemented finding the optimal water temperature parameter set for Hapcheon dam reservoir using CE-QUAL-W2 model. In particular the sensitivity analysis was carried out for four water temperature parameters of wind sheltering coefficient (WSC), radiation heat coefficient (BETA), light extinction coefficient (EXH2O), heat exchange coefficient at the channel bed (CBHE). Firstly, WSC, BETA, EXH2O shows relatively high sensitivity in common during April to September, and CBHE does during August to November. Secondly, as a result of identifying depth range of parameter influence, BETA and EXH2O show 0~9 m and 8~14 m which is thermocline layer close to water surface, CBHE is deep layer 12 m away from bottom. Finally, applying annual or monthly optimal parameter sets indicates that the bias between two sets does not show much differences for WSC and CBHE parameters, but BETA and EXH2O parameters show $0.20^{\circ}C$ and $0.51^{\circ}C$ of monthly average biases for two parameter sets. In particular the bias reveals to be $0.4^{\circ}C$ and $1.09^{\circ}C$ during May and August that confirms the necessity of use of monthly parameters during that season. It is claimed that the current operational custom use of annual parameters in calibration of reservoir water quality model requires the improvement of using monthly parameters.