• Journal of Korean Society for Geospatial Information Science
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• v.23 no.1
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• pp.113-121
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• 2015

Remote sensing technology using a multi-spectral satellite imagery can be utilized for the analysis of urban heat island effect in large area. However, weather condition of Korea mostly has a lot of clouds and it makes periodical observation using time-series of satellite images difficult. For this reason, we proposed the analysis of urban heat island effect using time-series of Landsat TM images and ATC model. To analyze vegetation condition and urbanization, NDVI and NDBI were calculated from Landsat images. In addition, land surface temperature was calculated from thermal infrared images to estimate the parameters of ATC model. Furthermore, the parameters of ATC model were compared based on the land cover map created by Korean Ministry of Environment to analyze urban heat island effect relating to the pattern of land use and land cover. As a result of a correlation analysis between calculated spectral indices and parameters of ATC model, MAST had high correlation with NDVI and NDBI (-0.76 and 0.69, respectively) and YAST also had correlation with NDVI and NDBI (-0.53 and 0.42, respectively). By comparing the parameters of ATC model based on land cover map, urban area had higher MAST and YAST than agricultural land and grassland. In particular, residential areas, industrial areas, commercial areas and transportation facilities showed higher MAST than cultural facilities and public facilities. Moreover, residential areas, industrial areas and commercial areas had higher YAST than the other urban areas.

• Korean Journal of Optics and Photonics
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• v.22 no.4
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• pp.184-190
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• 2011

A compact imaging spectrometer (COMIS) was developed for a microsatellite STSAT-3. The satellite is now rescheduled to be launched into a low sun-synchronous Earth orbit (~700 km) by the end of 2012. Its main operational goal is the imaging of the Earth's surface and atmosphere with ground sampling distance of 27 m and 2 - 15 nm spectral resolution over visible and near infrared spectrum (0.4 - 1.05 ${\mu}m$). A flight model of COMIS was developed following an engineering model that had successfully demonstrated hyperspectral imaging capability and structural rigidity. In this paper we report the environmental test results of the flight model. The mechanical stiffness of the model was confirmed by a small shift of the natural frequency i.e., < 1% over 10 gRMS random vibration test. Electrical functions of the model were also tested without showing any anomalies during and after vacuum thermal cycling test with < $10^{-5}$ torr and $-30^{\circ}C\;-\;35^{\circ}C$. The imaging capability of the model, represented by a modulation transfer function (MTF) value at the Nyquist frequency, was also kept unvaried after all those environmental tests.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.101-104
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• 2006

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that can explain ElNINO effect to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpola. Front (SPF) dividing into the north and south part of the East sea, the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF,SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong '-' value, where KF had strong '+' value. The time of '+' and '-' value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking '+' value which time was March and October That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.

• Journal of the Korean Geographical Society
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• v.40
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• pp.1-13
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• 1989

The brightness temperature from NOAA AVHRR CH 4 images was examined for the metropolitan Seoul area, the capital city of Korea, to detect the characteristics of the urban heat island for this study. Surface data from 21 meteorological stations were compared with the brightness temperatures Through computer enhancement techniques, more than 20 heat islands could be recognized in South Korea, with 1 km spatii resolution at a scale of 1: 200, 00O(Fig. 3, 4 and 6). The result of the analysis of AVHRR CH 4 images over the metropolitan Seoul area can be summerized as follows (1) The pattern of brightness temperature distribution in the metropolitan Seoul area shows a relatively strong temperature contrast between urban and rural areas. There is some indication of the warm brightness temperature zone characterrizing built-up area including CBD, densely populated residential district and industrial zone. The cool brightness temperature is asociaed with the major hills such as Bukhan-san, Nam-san and Kwanak-san or with the major water bodies such as Han-gang, and reservoirs. Although the influence of the river and reservoirs is obvious in the brightness temperauture, that of small-scaled land use features such as parks in the cities is not features such as parks in the cities is not apperent. (2) One can find a linerar relationshop between the brightenss temperature and air temperature for 10 major cities, where the difference between two variables is larger in big cities. Though the coefficient value is 0.82, one can estimate that factors of the heat islands can not be explained only by the size of the cities. The magnitude of the horizontal brightness temperature differences between urban and rural area is found to be greater than that of horizontal air temperature difference in Korea. (3) Also one can find the high heat island intensity in some smaller cities such as Changwon(won(Tu-r=9.0$^{\circ}$C) and Po-hang(Tu-r==7.1$^{\circ}$~)T. he industrial location quotient of Chang-won is the second in the country and Po-hang the third. (4) A comparision of the enhanced thermal infrared imageries in 1986 and 1989, with the map at a scale of 1:200, 000 for the meotropolitan Seoul area showes the extent of possible urbanization changes. In the last three years, the heat islands have been extended in area. zone characterrizing built-up area including (5) Although the overall data base is small, the data in Fig. 3 suggest that brightness tempeautre could ge utilized for the study on the heat island characteristics. Satellite observations are required to study and monitor the impact of urban heat island on the climate and environment on global scale. This type of remote sensing provides a meams of monitoring the growth of urban and suburban aeas and its impact on the environment.