• Journal of the Korean Society for Marine Environment & Energy
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• v.5 no.4
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• pp.19-26
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• 2002

This is a brief report on the development of a system which provides fishing vessels with a real-time key information that can direct to regions of high fish density. Water temperature and Plankton distribution are the base parameters and various public information have been examined and summarized. The suface water temperature can be obtained from NOAA's high resolution infrared data base and the vertical water temperature can be obtained from TAO/TRITON's buoy near the equator and ARGOS's drifting buoy covering wider Pacific ocean. MODIS's data is also utilized for sea color information. A model data format is proposed and a few examples are demonstrated.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.99-102
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• 2012

지표면 온도는 토지피복의 상태, 식생의 분포 상태, 토양수분, 증발산 등의 영향으로 많은 차이를 가지게 되며, 지면-대기의 상호순환의 중요한 인자로써 기후모델 및 농업 등의 기본적인 데이터로 사용되고 있다. 이러한 지표면의 온도를 정확하게 파악하는 것은 수문학적 관점 및 기상적인 관점에서 매우 중요하다. 기존에 LST (Land Surface Temperature, 지표면온도), ET (EvapoTranspiration, 증발산), NDVI (Normalized Difference Vegetation Index, 정규식생지수) 등의 검증이 많이 이루어진 MODIS위성의 Terra/Aqua센서는 한반도를 스캔하고 지나갈 때의 순간적인 데이터를 산출된다. 공간적인 면에서는 많은 이점이 있으나 시간적인 면에서는 시간에 따른 인자들의 변동성을 파악 하는데는 많은 문제가 있다. 그렇기 때문에 시 공간적으로 변화양상을 측정 할 수 있는 정지궤도위성의 중요성이 대두되고 있다. 본 연구에서는 국내에서 2010년 6월 27일 발사된 정지궤도위성인 천리안의 데이터를 활용하였다. 천리안 위성은 기상 센서와 해양관측 센서 그리고 통신센서를 가진 위성이다. 천리안 위성의 기상 센서는 MTSAT-1 위성과 같은 적외선 센서를 탑재하고 있으며, 평시에는 15분 단위의 데이터를 산출하게 된다. 천리안에서 제공되는 많은 Product(강우강도, 해수면온도, 가강수량, 지구방출복사 등)는 수자원 및 기상에 관련된 데이터가 제공된다. 하지만 아직 검증이 많이 이루어지지 못하였다. 그래서 천리안 위성 데이터인 지표면 온도자료를 이용하여 천리안 위성의 효율성에 대해서 알아보고자 하며, 기존의 검증이 많이 이루어진 MODIS의 데이터와의 상관성을 분석하고 지상과의 관계를 검증 및 비교하여 천리안 위성의 활용성에 대해서 알아보려고 한다.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.403-406
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• 2006

An algorithm for detection of yellow sand aerosols has been developed with infrared bands. This algorithm is a hybrid algorithm that has used two methods combined. The first method used the differential absorption in brightness temperature difference between $11{\mu}m\;and\;12{\mu}m\;(BTD1)$. The radiation at $11{\mu}m$ is absorbed more than at $12{\mu}m$ when yellow sand is loaded in the atmosphere, whereas it will be the other way around when cloud is present. The second method uses the brightness temperature difference between $3.7{\mu}m\;and\;11{\mu}m(BTD2)$. This technique is sensitive to dust loading, which the BTD2 is enhanced by reflection of $3.7{\mu}m$ solar radiation. First the Principle Component Analysis (PCA), a form of eigenvector statistical analysis from the two methods, is performed and the aerosol pixel with the lowest 10% of the eigenvalue is eliminated. Then the aerosol index (AI) from the combination of BTD 1 and 2 is derived. We applied this method to Multi-functional Transport Satellite-l Replacement (MTSAT-1R) data and obtained that the derived AI showed remarkably good agreements with Ozone Mapping Instrument (OMI) AI and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth.

• Journal of Wetlands Research
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• v.13 no.3
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• pp.471-479
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• 2011

Evapotranspiration (ET) including evaporation from a land surface and transpiration from photosynthesis of vegetation is a hydrological factor that has an important role in water cycle. However, there is a limitation to understand it due to heterogeneity of land cover and vegetation. In this study, Mapping EvapoTRanspiration with Internalized Calibration (METRIC) model, one of the energy balance models, and MODerate resolution Imaging Spectroradiometer (MODIS) satellite based well-known Penman-Monteith algorithm were compared. Two ET maps were categorized and compared by land cover classification. The results represented overall applicability of the two models with the highest correlation coefficients in needleleaf and broadleaf forests. This study will be useful to estimate remote sensing based ET maps with high resolution and to figure out spatio-temporal variability and seasonal changes.

• Proceedings of the KSRS Conference
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• v.2
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• pp.664-667
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at 0.65 ${\mu}m$ $(R_{0.65})$ and the difference in brightness temperature between 3.7 ${\mu}m$ and 11 ${\mu}m$ $(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at 3.7 ${\mu}m$ $(T_{3.7})$, the temperature at 11 ${\mu}m$ $(T_{11})$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the nine airport areas except the Cheongju airport have revealed the accuracy of 60% in the daytime and 70% in the nighttime, based on statistical verification as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.102-114
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• 2006

This study aims to develop a method to analyze droughts in Nakdong river area. Satellite imagery can be applied to droughts monitoring because it can afford periodic data for large area for long time. In this study, supposing that evapotranspiration and NDVI are closely related to each other, we presented a method to estimate evapotranspiration in large area with NDVI from MODIS data and temperature. For the final analysis of droughts, water deficit is calculated by climatological water balance using the distribution of evapotranspiration and precipitation. As the results of this study, we improved the usability of satellite imagery, especially in drought analysis.

• Korean Journal of Remote Sensing
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• v.22 no.5
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• pp.373-377
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• 2006

Seasonal threshold values for fog detection over the ten airport areas in the Korean Peninsula have been derived, using the satellite-observed data of polar-orbit (Aqua/Terra MODIS) and geostationary (GOES-9) during two years. The values are obtained from reflectance at $0.65{\mu}m\;(R_{0.65})$ and the difference in brightness temperature between $3.7{\mu}m\;and\;11{\mu}m\;(T_{3.7-11})$. In order to examine the discrepancy between the threshold values of two kinds of satellites, the following parameters have been analyzed under the condition of daytime/nighttime and fog/clear-sky, utilizing their simultaneous observations over the Seoul Metropolitan Area. The parameters are the brightness temperature at $3.7{\mu}m\;(T_{3.7})$, the temperature at $11{\mu}m\;(T_{11}$, and $T_{3.7-11}$ for day and night. The $R_{0.65}$ data are additionally included in the daytime. The GOES-9 thresholds over the seven airport areas except the Cheongju airport have revealed the accuracy of 50% in the daytime and 70% in the nighttime, based on statistical verification for the independent samples as follows; FAR, POD and CSI. However, the accuracy decreases in the foggy cases with twilight, precipitation, short persistence, or the higher cloud above fog.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.159-159
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• 2016

북한 지역에서 시작되어 한반도의 금문댐까지 연결되는 임진강은 북한지역의 유출량 미계측으로 인해 유출량 산출에 많은 어려움이 있어왔다. 본 연구에서는 위성 데이터를 활용하여 미계측 유역의 유출량을 추정 할 수 있는 기법을 제시하였다. Satellite-derived Flow Signal (SDF)는 위성 기반 특정 지역의 유출 정보를 제공하며, JAXA의 GCOM-W1 위성에 탑재된 Advanced Microwave Scanning Radiometer 2(AMSR2) 센서에서 산출된다. 본 연구에서는 SDS 뿐 아니라 유출에 크게 관련이 있는 지표 토양수분 데이터와 식생인자를 임진강 유출 값을 예측하기 위한 입력 값으로 활용하였다. 토양수분 데이터는 Metop-A 위성에 탑재된 Advanced Scatterometer(ASCAT) 센서에서 산출되는 데이터를 활용하였으며, 식생데이터는 Aqua 위성에 탑재된 Moderate Resolution Imaging Spectroradiometer(MODIS) 센서에서 측정되는 Normalized Difference Vegetation Index(NDVI) 데이터를 활용하였다. 추가적으로 SDS, 토양수분, NDVI 데이터는 다양한 lag time으로 약 150여개의 입력데이터로 세분화되었다. 150개의 방대한 입력인자는 Partial Mutual Information(PMI) 방법을 통해 소수 중요 인자들로 간추려져 기계 학습 입력인자로 활용되었다. 기계학습에 있어서는 Support Vector Machine(SVM), Artificial Neural Network (ANN) 기법을 활용하였다. SVM, ANN을 통해 모델화된 유출데이터는 금문댐 유출데이터와 비교/분석되었다. SVM 기법 기반의 유출량은 실제 유출량과 0.73의 상관계수를 보여주었고, ANN 기법 기반의 유출량은 0.66의 상관계수를 결과를 나타내었다. 하지만 SVM 기반 유출데이터는 과소 산정 되는 경향을 보였으며, ANN 기법 기반의 유출량은 과대산정되는 결과가 산출되는 한계점이 있음을 파악할 수 있었다.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.573-587
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• 2019

A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.1-11
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• 2017

The main source of water pollution in Doam Lake is turbid incoming water from upland fields in the upper watershed. The large scale, elevation, and slope of this region means that it is inaccessible, and it is difficult to collect information and update data. Field survey results show that there is a difference between classification of upland fields and grasslands in the cadastral data and land-cover map. In this study, MODIS NDVI was calculated from May 2000 to September 2015 in order to improve classification accuracy of upland fields.