• Journal of Astronomy and Space Sciences
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• v.35 no.2
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• pp.105-109
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• 2018

El $Ni{\tilde{n}}o$ is the largest fluctuation in the climate system, and it can lead to effects influencing humans all over the world. An El $Ni{\tilde{n}}o$ occurs when sea surface temperatures in the central and eastern tropical Pacific Ocean become substantially higher than average. We investigated the change in sea surface temperature in the Pacific Ocean during the El $Ni{\tilde{n}}o$ period of 2015 and 2016 using the advanced very-high-resolution radiometer (AVHRR) of NOAA Satellites. We calculated anomalies of the Pacific equatorial sea surface temperature for the normal period of 1981-2010 to identify the variation of the 2015 El $Ni{\tilde{n}}o$ and warm water area. Generally, the warm water in the western tropical Pacific Ocean shifts eastward along the equator toward the coast of South America during an El $Ni{\tilde{n}}o$ period. However, we identified an additional warm water region in the $Ni{\tilde{n}}o$ 1+2 and Peru coastal area. This indicates that there are other factors that increase the sea surface temperature. In the future, we will study the heat coming from the bottom of the sea to understand the origin of the heat transport of the Pacific Ocean.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.296-298
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• 1999

Five institutions, which are very active in data utilization of environmental satellites NOAA and GMS, are connected via high speed networks to construct the databases based on the observations of A AVHRR (Advanced very High Resolution Radiometer) of NOAA satellite and VISSR (Visible and Infrared Scanning Radiometer) of GMS (Geostationary Meteorological Satellite) and to create scientific data sets for land, ocean and ,atmosphere. And vegetation index, sea surface temperature, cloud distribution maps and so on are generated by high speed and huge volume data Processing for studies on long term variations of land, ocean and atmosphere in Asia. In this paper the concept of this project and the activities at the Science University of Tokyo are briefly introduced

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.224-232
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• 2006

This study investigates to detect Sea Surface Temperature (SST) and land cover change after tide embankment construction using Landsat Thematic Mapper (TM) Thermal Infrared (TIR) band data at Shihwa Lake and surrounding area. SST measurement is important for studies of both the structure of the ocean and as the thermal boundary between the ocean and the atmosphere. Since 1970s, the derivation of SST by satellite remote sensing (RS) has been applied to earth surface using Advanced Very High Resolution Radiometer (AVHRR) and Landsat TM. However, AVHRR has restriction in deriving SST in the area whose shoreline is complicated like western coast in South Korea because of coarse spatial resolution. The TIR band of TM images can be used to detect SST change whose shoreline is complicated and narrow like the study site. Thus, multi-temporal TM images were used for SST change detection in this study.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.257-261
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• 1998

Two-dimensional wavelet spectrum analysis is applied to Advanced Very High Resolution Radiometer (AVHRR) images from the NOAA meteorological satellites in the area around Japan to unfold the horizontal structure of SST into space and scale (wavenumber), which can yield localized space-wavenumber information. The results reveal significantly new and previously unexplored insights on horizontal structure of sea surface temperature, which cannot be revealed using a traditional Fourier transform approach.

• Korean Journal of Remote Sensing
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• v.6 no.1
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• pp.25-37
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• 1990

Methods of geometric correction for the Advanced Very High Resolution Radiometer imagery of NOAA satellites were developed and applied to the software for image processing of meteorological satellite data. The software for finding the earth location of each scan position and the software for gridding on original imagery were dedigned. On the assumption of circular orbits and the spherical earth, the methods developed were sufficiently accurate in the purpose of most meteorological data analyses.

• Korean Journal of Remote Sensing
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• v.32 no.6
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• pp.703-719
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• 2016

We investigated the changes with temporal and spatial movements of cold water events in summer season around the East Sea of Korea. Several data analyses were performed based on the various environmental factors using satellite and in-situ (winds, air/sea surface temperatures) data in the summer season during 2013. For analyzing the influence of cold water life cycle we employed AVISO geostrophic current and daily Geostationary Ocean Color Imager (GOCI) chlorophyll concentration (chl) data. Also, we used daily Advanced Very High Resolution Radiometer-Sea Surface Temperature (AVHRR-SST) data to trace the movements of cold water events. We found out the cold water events occurred in the early summer season and disappeared in the late summer season, and the cold water life cycle is repeated in this period. Additionally, we could show that the chl were increased in late summer season due to the inertial influence of cold water zone.

• Korean Journal of Remote Sensing
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• v.12 no.1
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• pp.60-80
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• 1996

AVHRR(Advanced Very High Resolution Radiometer) on NOAA satellite provides data in five spectral, one in visible range, one in near infrared and three in thermal range. In this paper, application of NOAA/AVHRR data is studied for environment monitoring such as cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index, forest fire, flood, snow cover and so on. The analyses for cloud top temperature, surface temperature, albedo, sea surface temperature, vegetation index and forest fire showed reasonable agreement. But monitoring for flood and snow cover was uneasy due to the limitations such as cloud contamination, low spatial resolution. So this research had only simple purpose to identify well-defined waterbody for dynamic monitoring of flood. Based on development of these basic algorithms, we have a plan to further reseach for environment monitoring using AVHRR data.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.6
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• pp.571-581
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• 2015

Soil moisture content is generally accepted as an important factor to understand the process of crop growth and is the basis of earth system models for analysis and prediction of the crop condition. To continuously monitor soil moisture changes at kilometer scale, it is demanded to create high resolution data from the current, several tens of kilometers. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) from 10 km to 30 m resolution using a soil texture and field measurements that have a high correlation with the SMC. As a result, the soil moisture variations of both data (before and after downscaling) were identical, and the Root Mean Square Error (RMSE) of SMC exhibited the low values. Also, time series analyses showed that three kinds of SMC data (field measurement, original AMSR2, and downscaled AMSR2) had very similar temporal variations. Our method can be applied to downscaling of other soil variables and can contribute to monitoring small-scale changes of soil moisture by providing high resolution data.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• 한국공간정보시스템학회:학술대회논문집
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• 2007.06a
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• pp.162-168
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• 2007

기후변화는 강수유형, 기온상승과 일사량의 변화로 인한 증발산량의 변화, 유역 식생피복변화로 인한 지표-대기 관계의 변화와 같은 현상을 통해 지역 부존 수자원과 유출량에 큰 변화를 가져올 수 있다. 특히 지표면의 76%를 차지하고 있는 식생피복은 지표와 대기 사이의 물 순환과정에서 중요한 인자이다. 본 연구에서는 넓은 지역에 대한 식생피복의 파악이 용이한 NOAA 위성의 AVHRR (Advanced Very High Resolution Radiometer) 센서로부터 얻을 수 있는 정규화 식생지수 (Normalized Difference Vegetation Index, NDVI)를 통하여 현 식생정보를 정량화하였다. 이로부터 토지피복별 NDVI와 기상인자(기온, 강수량, 일조시간, 풍속, 습도) 사이의 상관관계를 분석하고, 이를 기후변화 시나리오에 의한 기상인자로 부터 토지피복에 따른 미래 NDVI를 추정하였다.