• The Korean Journal of Ecology
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• v.28 no.4
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• pp.215-222
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• 2005

MODIS (Moderate Resolution Image Spectrometer) is a core satellite sensor boarded on Terra and Aqua satellite of NASA Earth Observing System since 1999 and 2001, respectively. MODIS LAI, FPAR, and GPP provide useful means to monitor plant phonology and material cycles in terrestrial ecosystems. In this study, LAI, FPAR, and GPP in Korea were evaluated and errors associated with cloud contamination on MODIS pixels were eliminated for years $2001\sim2003$. Three-year means of cloud-corrected annual GPP were 1836, 1369, and 1460g C $m^{-2}y^{-1}$ for evergreen needleleaf forest, deciduous broadleaf forest, and mixed forest, respectively. The cloud-originated errors were 8.5%, 13.1%, and 8.4% for FPAR, LAI, and GPP, respectively. Summertime errors from June to September explained by 78% of the annual accumulative errors in GPP. This study indicates that cloud-originated errors should be mitigated for practical use of MODIS vegetation products to monitor seasonal and annual changes in plant phonology and vegetation production in Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.154-154
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• 2012

지표에서의 토양수분은 작은 구성비를 가짐에도 불구하고 여러 수문 현상을 연계하는 매우 중요한 인자로써 최근 관련 연구가 활발하게 진행되고 있다. 토양수분은 침투나 침루를 통하여 강우와 지하수를 연결하는 기능을 함과 동시에 강우사상에 따른 유출특성에 직접적인 영향을 미치며 증발산을 통하여 에너지 순환을 연결하는 중요한 기능을 한다. 토양수분을 측정하는 방법에는 세타 탐침(Theta Probe), 장력계, TDR(Time Domain Reflectrometry) 등이 이용되고 있으며, 광역 토양수분자료의 보다 정확한 공간 변동성의 관측을 위하여 항공원격탐사와 인공위성 원격탐사기술이 개발되어 적용되고 있다. 인공위성 영상은 자료의 분석이 간편하며, 공간자료이므로 공간 변화를 분석하는 데 있어 매우 편리하다. 그 중 MODIS(Moderate Resolution Imaging Spectroradiometer) 위성영상은 저해상도 영상으로 극궤도 위성인 Terra와 Aqua 위성에 장착되어 있으며, NASA에서 필요한 정보를 받아 사용할 수 있다. 본 연구에서는 유역의 물리적 지형자료와 같은 방대한 양의 자료 수집 없이도, 모형이 구축되면 인공위성자료와 강우자료만으로도 신뢰성 높은 결과를 단시간 내에 효율적으로 산정할 수 있는 자료 지향형 모형인 ANFIS(Adaptive Neuro-Fuzzy Inference System)를 사용하였다. 사용된 퍼지변수로는 시험유역의 토양수분 관측자료와 강수량 및 인공위성 자료인 MODIS NDVI(Normalize Difference Vegetation Index), MODIS LST(Land-Surface Temperature) 영상을 이용하였다. MODIS NDVI는 시간 해상도 8일, 공간해상도 250 인 Level 3 영상이며, MODIS LST는 시간 해상도 1일, 공간해상도 1 km인 Level 3 영상을 사용하였다. 위성자료를 사용하기 위해 Korea TM 좌표체계로 변환한 뒤, 토양수분 관측지점이 속한 각 셀의 속성값을 추출하였다. 위성자료와 수집된 자료 및 토양수분자료와의 관계를 분석하기 위하여 입력자료를 다양한 방법으로 구성하여 입력 변수를 생성하였다. 생성된 입력 변수와 ANFIS 모형을 연계하여 각각의 토양수분 산정모형을 구축하고 대상지점에 대한 토양수분을 산정 및 비교 분석하였다.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.301-304
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• 2008

Since longer wavelength microwave radiation can penetrate clouds, satellite passive microwave sensors can observe sea ice of the entire polar region on a daily basis. Thus, it is becoming popular to derive sea ice motion vectors from a pair of satellite passive microwave sensor images observed at one or few day interval. Usually, the accuracies of derived vectors are validated by comparing with the position data of drifting buoys. However, the number of buoys for validation is always quite limited compared to a large number of vectors derived from satellite images. In this study, the sea ice motion vectors automatically derived from pairs of AMSR-E 89GHz images (IFOV = 3.5 ${\times}$ 5.9km) by an image-to-image cross correlation were validated by comparing with sea ice motion vectors manually derived from pairs of cloudless MODIS images (IFOV=250 ${\times}$ 250m). Since AMSR-E and MODIS are both on the same Aqua satellite of NASA, the observation time of both sensors are the same. The relative errors of AMSR-E vectors against MODIS vectors were calculated. The accuracy validation has been conducted for 5 scenes. If we accept relative error of less than 30% as correct vectors, 75% to 92% of AMSR-E vectors derived from one scene were correct. On the other hand, the percentage of correct sea ice vectors derived from a pair of SSM/I 85GHz images (IFOV = 15 ${\times}$ 13km) observed nearly simultaneously with one of the AMSR-E images was 46%. The difference of the accuracy between AMSR-E and SSM/I is reflecting the difference of IFOV. The accuracies of H and V polarization were different from scene to scene, which may reflect the difference of sea ice distributions and their snow cover of each scene.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.39-55
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• 2019

In this study, we have proposed an improved method to detect forest fires by correcting the reflected signals of day images using the middle-wavelength infrared (MWIR) channel. The proposed method is allowed to remove the reflected signals only using the image itself without an existing data source such as a land-cover map or atmospheric data. It includes the processing steps for calculating a solar-reflected signal such as 1) a simple correction model of the atmospheric transmittance for the MWIR channel and 2) calculating the image-based reflectance. We tested the performance of the method using the MODIS product. When compared to the conventional MODIS fire detection algorithm (MOD14 collection 6), the total number of detected fires was improved by approximately 17%. Most of all, the detection of fires improved by approximately 30% in the high reflection areas of the images. Moreover, the false alarm caused by artificial objects was clearly reduced and a confidence level analysis of the undetected fires showed that the proposed method had much better performance. The proposed method would be applicable to most satellite sensors with MWIR and thermal infrared channels. Especially for geostationary satellites such as GOES-R, HIMAWARI-8/9 and GeoKompsat-2A, the short acquisition time would greatly improve the performance of the proposed fire detection algorithm because reflected signals in the geostationary satellite images frequently vary according to solar zenith angle.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1149-1151
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• 2003

We performed a validation study of the MODIS active fire detection algorithm using high resolution SPOT image as the reference data set. Fire with visible smoke plumes are detected in the SPOT scenes, while the hotspots in MODIS data are detected using NASA's new version 4 fire detection algorithm. The detection performance is characterized by the commission error rate (false alarms) and the omission error rate (undetected fires). In the Sumatra and Kalimantan study area, the commission rate and the omission rate are 27% and 34% respectively. False alarms are probably due to recently burnt areas with warm surfaces. False negative detection occur where there are long smoke plumes and where fires occur in densely vegetated areas.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.437-450
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• 2004

Extensive forest fire activities occurred across the border in Russia, particularly east of Lake Baikal between the Amur and Lena rivers in May 2003. These forest fires released large amounts of particulates and gases into the atmosphere, resulting in adverse effects on regional air quality and the global radiation budget. Smoke pollution from the Russian fires near Lake Baikal was transported to Korea through Mongolia and eastern China. On 20 May 2003, a number of large fires were burning in eastern Russian, producing a thick, widespread pall of smoke over much of Northeast Asia. In this study, separation technique was used for aerosol retrieval application with imagery from MODIS aboard TERRA satellites. MODIS true-color image shows the location of fires and the grayish color of the smoke plumes over Northeast Asia. Aerosol optical thckness (AOT) retrieved from the MODIS data were compared with fire hot spots, ground-based radiation data and TOMS -based aerosol index data. Large AOT, 2.0-5.0 was observed on 20 May 2003 over Korea due to the influence of the long range transport of smoke aerosol plume from the Russian fires, while surface observed fine mode of aerosol size distribution increased.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.3
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• pp.141-148
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• 2012

Food policy is considered as the most basic and central issue for all countries, while making efforts to keep each country's food sovereignty and enhance food self-sufficiency. In the case of Korea where the staple food is rice, the rice yield prediction is regarded as a very important task to cope with unstable food supply at a national level. In this study, Korean paddy Rice yield Prediction Model (KRPM) developed to predict the paddy rice yield using meteorological element and MODIS NDVI. A multiple linear regression analysis was carried out by using the NDVI extracted from satellite image. Six meteorological elements include average temperature; maximum temperature; minimum temperature; rainfall; accumulated rainfall and duration of sunshine. Concerning the evaluation for the applicability of the KRPM, the accuracy assessment was carried out through correlation analysis between predicted and provided data by the National Statistical Office of paddy rice yield in 2011. The 2011 predicted yield of paddy rice by KRPM was 505 kg/10a at whole country level and 487 kg/10a by agroclimatic zones using stepwise regression while the predicted value by KOrea Statistical Information Service was 532 kg/10a. The characteristics of changes in paddy rice yield according to NDVI and other meteorological elements were well reflected by the KRPM.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.128-128
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• 2019

증발산량은 수표면이나 토양면에서 수증기의 형태로, 대기중으로 방출되는 증발량과 식물의 엽면을 통해 지중의 물이 대기 중으로 방출되는 증산량의 합으로, 기상학과 수문학에 사용되는 중요한 농업기상 매개 변수이다. 증발산량을 관측하는 방법으로는 라이시미터 (Lysimeter)와 같은 관측장비를 통해 실제 증발산량을 측정하는 방법과, FAO-56 Penman-Monteith (PM)과 같은 증발산량 추정 알고리즘을 이용하여 산출하는 방법이 있다. 국내의 경우 기상관측소에서 수집한 데이터를 이용하여 증발산량 추정공식을 통해 증발산량을 산정하는 연구가 이루어졌으며, 위성영상에 기반하여 증발산을 추정하려는 연구가 진행되고 있다. 본 연구에서는 미국 항공우주국 (National Aeronautics and Space Administration, NASA)에서 추진하는 위성을 이용한 지구 전역의 장기관측 계획 EOS (Earth Observing System)에 의해 발사된 지구 관측 위성인 MODIS Terra 위성에서 제공되는 MOD16A2 위성영상을 사용하였다. MOD16A2 위성영상은 2001년부터 현재까지 500m의 픽셀 단위로 제공되는 8일 간격의 전지구 규모의 위성영상으로, 본 연구에서는 우리나라 관측소에서 관측된 기상인자를 PM 공식에 입력하여 산정된 증발산량 값과 MOD16A2 위성영상 데이터를 비교하여 우리나라 MOD16A2 위성영상 적용성 및 밭작물 가뭄분석에 적용하였다.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• 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.