• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.11a
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• pp.37-38
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• 2002

인류의 산업활동으로 인한 지표 및 대기환경 변화로 인하여 이에 대한 모니터링은 필수적인 요소가 되었다. 한반도 지역은 중국으로부터의 장거리이동 오염물질과 황사에 의한 영향이 증가하고 있으므로 이의 감시가 매우 절실하다. 위성자료를 이용한 대기환경모니터링 기술은 이러한 필요성을 충족시켜줄 수 있어 대기환경의 시·공간적 변수를 연구하는데 유용하게 사용되어 왔다. 미국의 NOAA는 인공위성(NOAA/AVHRR)을 이용하여 전지구적 규모로 에어로졸의 분포를 지속적으로 관측하고 있으며, 대기 중 에어로졸 입자가 기후변화에 직접 및 간접적으로 상당 수준 관련되어 있다는 것을 확인하였다. (중략)

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.61-72
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• 2008

Leaf area index (LAI) is a key biophysical variable influencing land surface processes such as photosynthesis, transpiration and energy balance, and is a required input to estimate evapotranspiration in various ecological and hydrological models. The development of more correct and useful LAIs estimation techniques is required by these importance, but LAIs had been assumed in most LAI research through simple relations with the normalized difference vegetation index (NDVI) because the field measurement is difficult on wide area. This paper is to evaluate the MODIS LAI Product's practical use by comparing with LAIs that is derived from NOAA AVHRR NDVIs and the 2 years (2003-2004) measured LAIs of Korea Forest Research Institute in Gyeongancheon watershed (561.12 $Km^2$). As a result, the MODIS LAIs of deciduous forests showed higher values about 14 % and 15~30 % than the measured LAIs and NOAA LAIs. In the year of 2003, the MODIS LAIs in coniferous forests were 5 % higher than the measured LAIs, and showed about 7 % differences comparing with the NOAA LAIs except April. These differences come from the insufficient field data measured in partial points of the target area, and the extracted reference data from MODIS LAIs include the limits of spatial resolution and the error of incorrect land cover classification. Thus, using the MODIS data by the proper correction with the measured data can be useful as an input data for ecological and hydrological models which offers the vegetation information and simulates the water balance of a given watershed.

• Korean Journal of Remote Sensing
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• v.16 no.3
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• pp.211-220
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• 2000

Even though recurring eddies at the terminal end of the East Korean Warm Current have been identified in the thermal infrared imagery from the NOAA/AVHRR sensor and ocean color data from Orbview-2/SeaWiFS sensor, it is difficult to make observation in the field regarding recurring eddies located around the Wonsan coastal area in North Korea. But we could get in situ data related to an eddy from an ARGOS satellite tracking drifter trapped in the eddy on January 4th, 1999. An ARGOS drifter, a NOAA satellite tracked buoy was trapped by the eddy during January 4th.March 18, 1999. The ARGOS drifter rotated 10 times per 72 days on the edge of the eddy located at $39^{\circ}N$, $129^{\circ}E$. The diameter of the eddy was about 100 km. The horizontal rotation velocity of the recurring cold-core anti-cyclonic eddy was 1.53 km/h(42 cm/sec). The sea surface temperatures of the eddy varied from $14.7^{\circ}C$ on January 5, 1999 to $9.6^{\circ}C$ on March 18,1999. To study the mechanism of the recurring eddy. we tried to find out the relationship between the vector of the drifter moving in the eddy and the wind vector in Sokcho and Ulleung Island located near the eddy in southern Korea, and the difference in sea level between Ulleung Island and Mukho. We hope the results of this study would be useful for calibration and validation data of simulation and numerical modeling studies of the recurring eddy.

• 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.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.165-173
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• 2010

A cloud detection method is introduced to improve the reliability of NOAA/AVHRR Sea Surface Temperature (SST) data processed during the daytime and nighttime in the TeraScan System. In daytime, the channels 2 and 4 are used to detect a cloud using the three tests, which are spatial uniformity tests of brightness temperature (infrared channel 4) and channel 2 albedo, and reflectivity threshold test for visible channel 2. Meanwhile, the nighttime cloud detection tests are performed by using the channels 3 and 4, because the channel 2 data are not available in nighttime. This process include the dual channel brightness temperature difference (ch3 - ch4) and infrared channel brightness temperature threshold tests. For a comparison of daytime and nighttime SST images, two data used here are obtained at 0:28 (UTC) and 21:00 (UTC) on May 13, 2009. 6 parameters was tested to understand the factors that affect a cloud masking in and around Korean Peninsula. In daytime, the thresholds for ch2_max cover a range 3 through 8, and ch4_delta and ch2_delta are fixed on 5 and 2, respectively. In nighttime, the threshold range of ch3_minus_ch4 is from -1 to 0, and ch4_delta and min_ch4_temp have the fixed thresholds with 3.5 and 0, respectively. It is acceptable that the resulted images represent a reliability of SST according to the change of cloud masking area by each level. In the future, the accuracy of SST will be verified, and an assimilation method for SST data should be tested for a reliability improvement considering an atmospheric characteristic of research area around Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.37 no.8
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• pp.631-641
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• 2004

The objective of this study is to test the applicability of SLURP (Semi-distributed Land Use-based Runoff Process) on Soyanggang-dam watershed. SLURP model is a conceptual semi-distributed form model that can be used to examine irrigation plan and the effects of proposed changes in water management within a basin or to see what effects external factors such as climate change or changing land cover might have on various water users. Topographical parameters were derived from DEM using TOPAZ and SLURPAZ. Monthly NDVIs were calculated from multi-temporal NOAA/AVHRR images during four years (1998 ∼ 2001). Weather elements (dew-point temperature, solar radiation, maximum/minimum temperature and relative humidify) were obtained from five meteorological stations within and near the study area. To simulate daily hydrograph during 1998 ∼ 2001, the model parameters of each land cover class were optimized by sensitivity analysis and SCE-UA method. Test result of SLURP was summarized by various statistics method (WMO volume error, Nash-Sutcliffe efficiency, mean error and coefficient of variation).

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1940-1944
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• 2006

현지관측을 통한 지속적이고 광범위한 지역에 대해 정확하고 정밀하게 조사하여 종합적인 분석과 예측, 결정과정에 있어서, 복잡한 해양의 특성, 여러가지 조사 작업상의 난점, 경제적, 시간적으로 많은 어려움이 따르게 된다. 하지만, 위성원격탐사와 GIS를 이용한 해양환경파악기법은 현지관측에서 얻을 수 있는 제한적인 자료이외의 다량의 자료를 정성 및 정량적으로 데이터베이스화하여 분석함과 동시에 가시화함으로써 해양개발로 인해 불가피하게 초래될 수밖에 없는 환경을 보다 정확하게, 객관적으로 분석하여 장기적으로 예측할 수 있는 고도화된 환경조사 및 평가 기술이라고 할 수 있다. 본 연구에서는 고해상도 위성자료인 Landsat TM 영상과 NOAA AVHRR 자료를 이용하여 수온 및 클로로필을 추출하였으며, GIS를 이용하여 현지관측자료 및 수치해도를 기초로 공간분포도를 작성함으로서 그 외의 수질환경요소를 산출하였다. 위성영상분석은 현장조사와 같은 시점의 Landsat TM 위성영상을 획득하여, 위성 영상은 지구의 곡률과 자전, 위성체의 자세와 고도 및 속도, 그리고 센서의 기하 특성으로 인하여 실제의 지형에 대하여 기하학적 왜곡을 가지고 있으므로 지형도에서 지상기준점(Ground Control Point, GCP)를 추출하여 ERDAS Imagine으로 UTM좌표체계에 따른 기하보정(Geometric Correction)을 실시하였으며, 동일한 시기의 NOAA AVHRR영상을 데이터로 처리하여 수온자료를 추출하였다. 표층수온과 현장관측에 의한 클로로필을 수치 지도화하기 위하여 열적외선영역인 TM band 6의 분광특성값(Digital Number)과 동일한 위치의 수온자료를 기초로 회귀분석을 실시함으로써 수온추출 알고리즘을 도출하여, 분석데이터의 신뢰도를 검증하였으며, 수온, 클로로필, 투명도 등을 위성원격탐사 자료와 GIS를 이용하여 공간분석을 실시하고, 공간분포도를 작성함으로써 대상해역의 해양환경을 파악하였다. 본 연구결과, 분석된 위성자료가 현장조사에 의한 검증이 이루어지지 않을 경우, 영상자료분석을 통한 표층수온 추출은 대기 중의 수증기와 에어로졸에 의한 계산치의 오차가 반영되기 때문에 실측치 보다 낮게 평가 될 수 있으므로, 반드시 이에 대한 검증이 필요함을 알 수 있었다. 현지관측에 비해 막대한 비용과 시간을 절약할 수 있는 위성영상해석방법을 이용한 방법은 해양수질파악이 가능할 것으로 판단되며, GIS를 이용하여 다양하고 복잡한 자료를 데이터베이스화함으로써 가시화하고, 이를 기초로 공간분석을 실시함으로써 환경요소별 공간분포에 대한 파악을 통해 수치모형실험을 이용한 각종 환경영향의 평가 및 예측을 위한 기초자료로 이용이 가능할 것으로 사료된다.

• Journal of Korea Water Resources Association
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• v.36 no.5
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• pp.839-849
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• 2003

Drought is one of the major environmental disasters. Weather data, particularity rainfall, are currently the primary source of information widely used for drought monitoring. However, weather data are often from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely drought detection. Data from remote sensing platforms can be used to complements weather data in drought. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI)-based vegetation condition index(VCI) were used in this study These indices showed their excellent ability to detect vegetation stress due to drought. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the VCI index.

• Journal of the Korean Geographical Society
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• v.9
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• pp.67-75
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• 1974

The vegetation activity of the Korean peninsula has been monitored temporal variations through a satellite remote sensing and the vegetation index was used to set up the vegetation data map of Korea. The AVHRR data sent by the NOAA-14 satellite was collected for 8 months between April and November, 1997 to calculate the normalized difference vegetation index(NDVI) which was combined the MVC(Maximum Value Composite). Then this NDVI composite map was prepared to review the temporal variations in the vegetation activity. The NDVI has been subject to the unsupervised classification for the growing season between May and October. And the vegetation type is divided into five classes ; urban, bare soil, grass, farming land, deciduous forest and coniferous forest. The unsupervised classificaion of vegetation distribution in the Korean Peninsula shows that the urban and bare soil take 4.14% of total national area, grass 4.49%, farming land 27.54%, deciduous forest 25.61% and coniferous forest 38.22%.

• Journal of Korea Water Resources Association
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• v.40 no.8
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• pp.617-628
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• 2007

The purpose of this paper is to prepare snowmelt parameters using RS and GIS and to assess the snowmelt impact in SLURP (Semi-distributed Land Use-based Runoff Process) model for Chungju-Dam watershed $(6,661.5km^2)$. Three sets of NOAA AVHRR images (1998-1999, 2000-2001, 2001-2002) were analyzed to prepare snow-related data of the model during winter period. Snow cover areas were extracted using 1, 3 and 4 channels, and the snow depth was spatially interpolated using snowfall data of ground meteorological stations. With the snowmelt parameters, DEM (Digital Elevation Model), land cover, NDVI (Normalized Difference Vegetation Index) and weather data, the model was calibrated for 3 years (1998, 2000, 2001), and verified for 1 year (1999) using the calibrated parameters. The average Nash-Sutcliffe efficiencies for 4 years (1998-2001) discharge comparison with and without snowmelt parameters were 0.76 and 0.73 for the full period, and 0.57 and 0.19 for the period of January to May. The results showed that the spatially prepared snow-related data reduced the calibration effort and enhanced the model results.