• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.175-181
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• 1999

A recurring eddy which located at the terminal end of the Korean East Warm Current was captured on ocean color and sea surface temperature imagery from satellite in spring and autumn. During late April, 1997 thermal infrared imagery from the NOAA AVHRR sensor and ocean color data from the Japanese ADEOS-I OCTS sensor, revealed this feature. The cold core had elevated chlorophyll concentrations, based on OCTS estimates, of greater than 3 mg/m$^3$ while the warmer surrounding waters had chlorophyll concentrations of 1 mg/m$^3$ or less. The elevated cholophyll accociated with this eddy has not been previously described. The eddy is also evident in SST images from autumn, but the SST in the core is warmer than in spring, and the warm jet flowing to the west of the eddy is also warmer is autumn compared to spring. A reccurring eddy and the high chlorophyll_a concentration area which surround around the eddy show on NOAA and SeaWiFS images in March 2, 1998. The eddy forms at the northern extent of the Korean East Warm Current as those waters collide with the cold, south-flowing Liman Current over a topographic shelf about 1500 m deep. This region of the eddy formation appears to have a strong connection with the dynamics of the western part of the polar front eddy field that dominates surface mesoscale structure in the central East (Japan) Sea. Interaction of the eddy with ARGOW tracked drifters, and evidence for its persistence are discussed.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.2 s.13
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• pp.61-69
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• 2004

Drought is one of the mai or 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. Therefore, data obtained from the Advanced Very High Resolution Radiometer(AVHRR) sensor boarded on the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring. The normalized difference vegetation index(NDVI) and vegetation condition index(VCI) were used in this study. Also, a simple method to detect drought Is Proposed based on climatic water balance using NOAA/AVHRR data. The results clearly show that temporal and spatial characteristics of drought in Korea can be detected and mapped by the moisture index.

• 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.

• Journal of the Korean earth science society
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• v.22 no.2
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• pp.138-146
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• 2001

The land cover over Korean peninsula was classified using a multi-temporal NOAA/AVHRR (Advanced Very High Resolution Radiometer) data. Four types of phenological data derived from the 10-day composited NDVI (Normalized Differences Vegetation Index), maximum and annual mean land surface temperature, and topographical data were used not only reducing the data volume but also increasing the accuracy of classification. Self organizing feature map (SOFM), a kind of neural network technique, was used for the clustering of satellite data. We used a decision tree for the classification of the clusters. When we compared the classification results with the time series of NDVI and some other available ground truth data, the urban, agricultural area, deciduous tree and evergreen tree were clearly classified.

• Journal of Environmental Science International
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• v.17 no.9
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• pp.949-956
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• 2008

The data of temperature, chlorophyll a, phytoplankton and NOAA/AVHRR satellite data were analyzed about 7 stations around Wando Island area on August 30, 2005. The sea water temperature range was from $15.19^{\circ}C$ to $24.97^{\circ}C$, and there was a cold water mass from the station 1 to 5 around the outside of Chungsando Island, the water temperature was lower at the bottom than surface. The salinity was $32.41{\sim}34.03$, DO was $7.40{\sim}9.14mg/L$, but the concentration of chlorophyll a was 1ug/L higher at the bottom than surface. Total phytoplankton appeared from the whole stations were 47 genus, 80 species and diatoms were dominant. A lot of dinoflagellates Ceratium forca and diatoms Thalassithrix spp. mostly appeared in the cold water mass were turned up from the station 1 to 5. 4 groups of phytoplankton clusters were shown in the surface, and 3 groups of phytoplankton clusters were shown at the bottom according to the water temperature. On the ground of the result analyzed with NOAA/AVHRR satellite data, the SST around Wando Island was $22{\sim}25^{\circ}C$, it was formed by thermohaline front latitudinally

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.237-242
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• 1999

As one of the key parameters to determine $CO_2$ flux between air - sea interface, it is quite important to know p$CO_2$, which has involved much uncertainty, mainly due to the complex variations of sea surface p$CO_2$ and the paucity of samples, made in ocean. In order to improve the interrelationship between partial pressure (p$CO_2$) and different physical and biochemical parameters in global sea surface water, a new empirical relation is established to correlate and parameterize p$CO_2$ in the mixed layer using the data from recent WOCE cruises. Meanwhile, by new empirical relation, abundant historical hydrographic and nutrients ship data, Levitus data set and NOAA/AVHRR(SST), p$CO_2$ have been accumulated and applied. Then effort has to be made fur promotion of this study to correlate and parameterize p$CO_2$ in the mixed Layer with different physical and biochemical parameters. and further attribute this huge historical data sets and NOAA/AVHRR(SST) data to estimate p$CO_2$. In this paper we analyzed more interrelationship between the model and ship/satellite data set. Finally, the inter-annual variations of p$CO_2$ in sea are presented and discussed.

• 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 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 KSRS Conference
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• v.2
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• pp.1027-1030
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• 2006

Development of diurnal warming in the open Okhotsk Sea during the daytime and calm conditions was studied using sea surface temperature (SST) fields retrieved from NOAA AVHRR, Terra and Aqua MODIS, Aqua AMSR-E and ADEOS-II AMSR data. Sea surface wind fields were estimated from AMSR-E/AMSR measurements as well as were obtained from QuikSCAT scatterometer. Weak winds and cloudless conditions were observed in the central area of anticyclone, which moved slowly on 28-30 June 2003 east off Sakhalin. The area where the amplitude of the diurnal SST signal ${\Delta}T$ was significant also shifted slowly and had or circular or elongated shape. The ${\Delta}T$ was estimated relative to the SST values in the areas surrounding the centre of anticyclone where wind speed W exceeded 5- 6 m/s. The diurnal variations of SST, day-night differences were computed using NOAA-12 and NOAA-16 AVHRRderived data. Analysis of simultaneous SST and W fields showed that the increase of W from 0 to 5-6 m/s causes the decrease of ${\Delta}T$ to zero. Maximum warming exceeded $8^{\circ}C$ and was observed in the centre of anticyclone where W = 0 m/s. So strong heating was likely due to the increased chlorophyll a concentration in the area under study that follows from analysis of satellite ocean colour data.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.291-296
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• 2003

This study estimated surface temperature by using split-window technique and NOAA/AVHRR data was used. For surface monitoring, cloud masking procedure was carried out using threshold algorithm. The daily maximum air temperature is estimated by multiple regression method using independent variables such as satellite-derived surface temperature, EDD, and latitude. When the EDD data added, the highest correlation shown. This indicates that EDD data is the necessary element for estimation of the daily maximum air temperature. We derived correlation and experience equation by three approaching method to estimate daily maximum air temperature. 1) non-considering landcover method as season, 2) considering landcover method as season, and 3) just method as landcover. The last approaching method shows the highest correlation. So cross-validation procedure was used in third method for validation of the estimated value. For all landcover type 5, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.97, intercept=-0.30, R$^2$=0.84, RMSE=4.24$^{\circ}C$). Also, for all landcover type 7, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.993, Intercept=0.062, R$^2$=0.84, RMSE=4.43$^{\circ}C$).