• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.4
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• pp.331-337
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• 2011

We described for the production of cloud-free satellite sea surface temperature(SST) data around Northeast Asian using NOAA AVHRR(Advanced Very High Resolution Radiometer) SST data during 1990-2005. As a result of Markov model, it was found that the value of Markov coefficient in the strong current region such as Kuroshio region showed smaller than that in the weak current. The variations of average SST and regional difference of seasonal day-to-day SST in spring and fall were larger than those in summer and winter. In particular, the distribution of the regional difference appeared large in the vicinity of continental in spring and fall. The difference of seasonal day-to-day SST was also small in Kuroshio region and southern part of East Sea due to the heat advection by warm currents.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.845-854
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• 2006

Establishment of snowmelt factors is necessary to simulate stream flow using snowmelt models during snowmelt periods. The few observed data related snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. The objective of this study was to extract snowmelt factors using RS, GIS technique and meteorological data. Snow cover maps were derived from NOAA/AVHRR images for the winter seasons from 1997 to 2003. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation station. Depletion curves of snowmelt area were described from the linear regression equations of each year between the average temperature and snow cover area in Soyanggang-dam and chungju-dam watershed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.177-185
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• 2008

Accurate monitoring of snow cover is a key component for studying climate and global as well as for daily weather forecasting and snowmelt runoff modelling. The few observed data related to snowmelt was the major cause of difficulty in extracting snowmelt factors such as snow cover area, snow depth and depletion curve. Remote sensing technology is very effective to observe a wide area. Although many researchers have used remote sensing for snow observation, there were a few discussions on the characteristics of spatial and temporal variation. Snow cover maps were derived from NOAA AVHRR images for the winter seasons from 1997 to 2006. Distributed snow depth was mapped by overlapping between snow cover maps and interpolated snowfall maps from 69 meteorological observation stations. Model parameters (Snow Cover Area: SCA, snow depth, Snow cover Depletion Curve: SDC) were built for 7 major watersheds in South Korea. The decrease pattern of SCA for time (day) was expressed as exponentially decay function, and the determination coefficient was ranged from 0.46 to 0.88. The SCA decreased 70% to 100% from the maximum SCA when 10 days passed.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.386-389
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• 1999

In this study, visible and near infrared channels of NOAA/AVHRR data were used to classify land use and vegetation types over Korean peninsula. Analyzing forest stand structures and prediction of forest productivity using satellite data were also reviewed. Land use and land cover classification was made by unsupervised clustering methods. After monthly Normalized Difference Vegetation Index (NDVI) composite images were derived from April to November 1998, the derived composite images were used as temporal feature vector's in this clustering analysis. Visually interpreted, the classification result was satisfactory in overall for it matched well with the general land cover patterns. But subclassification of forests into coniferous, deciduous, and mixed forests were much confused due to the effects of low ground resolution of AVHRR data and without defined classification scheme. To investigate into the forest stand structures, digital forest type maps were used as an ancillary data. Forest type maps, which were compiled and digitalized by Forestry Research Institute, were registered to AVHRR image coordinates. Two data sets were compared and percent forest cover over whole region was estimated by multiple regression analysis. Using this method, other forest stand structure characteristics within the primary data pixels are expected to be extracted and estimated.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.869-872
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• 2003

The thermal contamination of the Younggwang coastal marine ecosystem has been investigated using space borne thermal infrared data acquired over the period 1985-2003 by the Landsat and NOAA satellites. The analysis of AVHRR data brought out the general pattern and extension of thermal plume while TM data yielded more accurate information about the plume shape, dimension, dispersion direction etc. The examination of sea surface temperature (SST) computed from these images clearly indicates that the thermal plume extends 70 to100km southward during summer and 50 to70km northwestward during winter monsoons. The maximum plume temperature was 29$^{\circ}C$ in summer and 12$^{\circ}C$ in winter. The comparative analysis shows that the temperature retrieved from TM is slightly higher (1.8$^{\circ}C$, 3$^{\circ}C$ and 2.2$^{\circ}C$ for the images of 98/11/10, 99/05/05 and 99/05/21 respectively) than those derived from AVHRR data. The correlation coefficient between the TM-derived SST and AVHRR-derived SST was 0.72.

• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.164-169
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• 2008

한국해양연구원에서 수신한 자료인 NOAA 12, 16, 17, 18호등의 Advanced Very High Resolution Radiometer(AVHRR) 센서자료와 국립조사원에서 제공하는 해양실측자료인 정선 관측 자료를 이용하여 두 가지의 알고리즘 적용을 통하여 비교 및 분석을 해보고자 한다. 연구 기간은 2006년 1월부터 4월 자료 중 구름의 영향이 없는 영상에서 실측자료와 동일한 날짜 총 107개의 정점 값을 추출하였다. 위성 자료에서 해수면 온도 추출방법은 split window 방법으로, 고정계수 값을 사용하는 linear algorithm(MCSST), nonlinear algorithm(NLMCSST)을 이용하였다. 연구 지역은 동해, 황해, 남해 지역에 대한 지역별로 두 알고리즘을 비교 적용하였다. 전 해역의 값을 이용하여 위성자료와 실측자료를 비교 분석한 결과 linear algorithm방법의 평균 오차 값은 0.71$^{\circ}C$이고 상관도는 1%이고, nonlinear 방법의 오차 값은 0.35$^{\circ}C$ 상관도는 1%로 나타났다. 해역별로는 linear한 알고리즘을 적용하여 동해는(ES)는 R=1, 오차 값은 0.37$^{\circ}C$ 황해(YS)는 R=0.99 오차 값은 0.125$^{\circ}C$ 남해(SS)는 R=0.99 오차 값은 1.2$^{\circ}C$보였다. nonlinear한 알고리즘을 적용하여 동해는(ES)는 R=1, 오차 값은 0.4$^{\circ}C$ 황해(YS)는 R=0.99 오차 값은 0.13$^{\circ}C$ 남해(SS)는 R=0.99 오차 값은 0.82$^{\circ}C$의 결과를 보여 주었다. 동해와 황해지역은 linear한 알고리즘을 적용한 결과가 실측자료와의 오차 값이 작았고, 남해지역은 linear한 알고리즘을 적용한 결과보다 nonlinear 알고리즘을 적용한 것이 작은 오차 값을 보여주었다. 이는 남해 해역의 자료가 대기의 상태나 다른 영향을 받아 해수면온도 값이 추정된 것으로 보여 진다. 해역별로 최적화된 알고리즘을 적용하여 해수면온도의 산출을 통해서 위성자료의 정밀도 지구환경변화 모니터링 등 많은 연구에 위성자료의 활용이 증대될 것으로 기대한다.

• Korean Journal of Remote Sensing
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• v.9 no.1
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• pp.79-93
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• 1993

The relative geostrophic velocity is estimated by using the MCSST(Multi-Channel Sea Surface Temperature) from a NOAA/AVHRR image and applied to the Korea Strait. Remote sensing technique can play a useful role to research for oceanic phenomena because of its synoptic, simultaneous and repetitive viewing. The high resolution data of AVHRR can determine the geostrophic flow more precisely than the hydrographic data on shipboard. As a result of research, the relative geostrophic velocity in the weatern channel of the Korea Strait is the strongest in the trough area and its maximum speed is about 23.8cm/sec in April, 1992. But this results include the error due to neglecting the effect of salinity in estimation the geopotential anomaly. The geostrophic volume transport through the western channel of the Korea Strait is the largest between trough area and the Tsushima Island.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.58-69
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• 2007

The vegetation area that occupies 76% in land surface of the earth can give a considerable impact on water resources, environment and ecological system by future climate change. The purpose of this study is to predict future vegetation cover information from NDVI (Normalized Difference Vegetation Index) extracted from satellite images. Current vegetation information was prepared from monthly NDVI (March to November) extracted from NOAA AVHRR (1994 - 2004) and Terra MODIS (2000 - 2004) satellite images. The NDVI values of MODIS for 5 years were 20% higher than those of NOAA. The interrelation between NDVIs and monthly averaged climate factors (daily mean, maximum and minimum temperature, rainfall, sunshine hour, wind velocity, and relative humidity) for 5 river basins of South Korea showed that the monthly NDVIs had high relationship with monthly averaged temperature. By linear regression, the future NDVIs were estimated using the future mean temperature of CCCma CGCM2 A2 and B2 climate change scenario. The future vegetation information by NOAA NDVI showed little difference in peak value of NDVI, but the peak time was shifted from July to August and maintained high NDVIs to October while the present NDVI decrease from September. The future MODIS NDVIs showed about 5% increase comparing with the present NDVIs from July to August.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.761-765
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• 2005

원격탐사 기법은 식생 및 토지 이용과 같은 지형조건과 관련된 증발산량을 산정하기 위한 하나의 수단으로 효과적으로 이용될 수 있다. 지표면에서 발생되는 증발산량을 지배하는 인자는 기온, 습도, 바람, 일사량 및 토양조건 등 매우 복잡하게 구성된다. 식생은 그 지점의 증발산량에 영향을 주고 있으며, 증발산량을 지배하는 복잡한 인자는 식생의 성장조건에 직접적으로 영향을 미친다. 결국 증발산량과 식생조건 사이에는 강한 상관관계가 성립할 수 있음을 예상할 수 있다. 비교적 넓은 지점에 대한 식생상태의 파악을 위해서는 NOAA/AVHRR 자료가 효과적으로 이용될 수 있으며, 이로부터 얻어지는 식생지수(NDVI)를 이용함으로서 증발산량과 NDVI 사이의 강한 상관관계를 생각할 수 있다. 입력자료로 이용되는 기상자료가 많을수록 자료의 획득 및 처리에 많은 시간이 요구되므로 본 연구에서는 기상자료 중 비교적 쉽고 정확한 값을 얻을 수 있는 기온자료만을 채택하여 분석 시의 번거로움을 최소화하였다. 본 연구에서는 위성자료와 기상자료 중 가장 획득이 용이한 기온자료를 조합하는 간편한 방법에 의한 실제증발산량 산정방법을 제안한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1980-1984
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• 2006

융설 모형을 이용하여 융설 기간 동안의 하천유출량을 모의하기 위해서는 융설 관련 매개변수의 정립이 반드시 필요하다. 우리나라의 경우 관측 자료의 부족으로 인하여 적설분포, 적설심, 적설면적감소곡선과 같은 융설 관련 매개변수의 추출이 불가능 하였다. 본 연구에서는 1997년부터 2003년까지의 겨울철(11월-4월) NOAA/AVHRR 위성영상을 이용하여 한반도의 적설분포도를 추출하고 기상청의 69개소 유인지상기상관측소의 기상자료 중 최심적설심 자료로서 공간내삽법을 통하여 동일한 기간의 최심적설심 분포도를 작성한 후 적설분포도와 중첩하여 남한의 적설심 분포도를 추출하였다. 또한, 적설면적감소곡선은 소양강댐과 충주댐 유역으로 대상으로 평균기온과 적설면적과의 상관관계로부터 각 연도별 선형회귀식을 추출하여 적설면적감소곡선을 작성하였다.