Ms. Minji Seo Profile

Minji Seo

at Pukyong National Univ

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Publications (3)

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 | 19 October 2016 Paper

Analysis on long-term variability of sea ice albedo and its relationship with sea ice concentration over Antarctica

Minji Seo, Hyun-cheol Kim, Noh-hun Seong, Chaeyoung Kwon, Honghee Kim, Kyung-Soo Han

Proceedings Volume 9999, 99990T (2016) https://doi.org/10.1117/12.2240156

KEYWORDS: Analytical research, Satellites, Climate change, Climatology, Curium, Time series analysis, Spatial resolution, Positive feedback, Remote sensing, Environmental sensing

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Proceedings Article | 19 October 2016 Paper

Correlation analysis between variability pattern of TPW and climate variables

Darae Lee, Kyung-Soo Han, Chaeyoung Kwon, Minji Seo, Kyeong-sang Lee

Proceedings Volume 10001, 1000111 (2016) https://doi.org/10.1117/12.2241772

KEYWORDS: Climatology, Electroluminescence, Absorption, Earth observing sensors, Satellites, Time series analysis, MODIS, Analytical research, Climate change, Atmospheric monitoring

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