Mr. Chang-Suk Lee Profile

Chang-Suk Lee

at Pukyong National Univ

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Publications (4)

Proceedings Article | 25 October 2016 Paper

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

Kyeong-sang Lee, Sungwon Choi, Minji Seo, Chang suk Lee, Noh-hun Seong, Kyung-Soo Han

Proceedings Volume 9998, 999820 (2016) https://doi.org/10.1117/12.2241732

KEYWORDS: Snow cover, Reflectivity, Clouds, MODIS, RGB color model, Satellites, Detection and tracking algorithms, Data modeling, Molybdenum, Climatology

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Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth’s energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 ~ 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer’s Accuracy), UA (User’s Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Proceedings Article | 24 October 2013 Paper

An influence assessment of GSICS correction using sea surface temperature from geostationary satellite: COMS

Eun-Bin Park, Kyung-Soo Han, Jae-il Cho, Chang-Suk Lee, In-Hwan Kim, Kyoung-Jin Pi, Jae-Hyun Ryu, Jung-Mok Ha

Proceedings Volume 8893, 88931N (2013) https://doi.org/10.1117/12.2029142

KEYWORDS: Satellites, Meteorological satellites, Sensors, Infrared imaging, Calibration, Environmental sensing, Infrared sensors, Satellite communications, Climate change, Infrared radiation

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Proceedings Article | 16 October 2013 Paper

11-year variability of summer snow cover extent over Himalayas

Jung-Mok Ha, Kyung-Soo Han, Jae-Il Cho, Chang-Suk Lee, Kyoung-jin Pi, In-Hwan Kim, Jae-Hyun Ryu, Eun-Bin Park

Proceedings Volume 8887, 88871K (2013) https://doi.org/10.1117/12.2029146

KEYWORDS: Snow cover, Climatology, MODIS, Climate change, Clouds, Agriculture, Satellites, Meteorology, Reflectivity, Water

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Proceedings Article | 16 October 2013 Paper

Estimation of maximum air temperature using COMS data in Northeast Asia

Jae-Hyun Ryu, Kyung-Soo Han, Jae-Il Cho, Chang-Suk Lee, In-Hwan Kim, Kyoung-Jin Pi, Jung-Mok Ha, Eun-Bin Park

Proceedings Volume 8887, 88871X (2013) https://doi.org/10.1117/12.2029143

KEYWORDS: Tantalum, Satellites, Meteorology, Meteorological satellites, Climatology, Vegetation, Temperature metrology, Ecosystems, Data analysis, Remote sensing

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