• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.90-98
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• 2011

The recognition and classification of paddy rice disease are of major importance to the technical and economical aspect of agricultural industry over the world. Computer vision techniques are used to diagnose rice diseases and to efficiently manage crops. Segmentation of lesions is the most important technique to detect paddy rice disease early and accurately. A new Gaussian Mean (GM) method was proposed to segment paddy rice diseases in various color spaces. Different color spaces produced different results in segmenting paddy diseases. Thus, this empirical study was conducted with the motivation to determine which color space is best for segmentation of rice disease. It included five color spaces; NTSC, CIE, YCbCr, HSV and the normalized RGB(NRGB). The results showed that YCbCr was the best color space for optimal segmentation of the disease lesions with 98.0% of accuracy. Furthermore, the proposed method demonstrated that diseases lesions of paddy rice can be segmented automatically and robustly.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.71-79
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• 2014

Most researches have created the impervious surface map by using low-spatial-resolution satellite imagery and are inefficient to generate the object-based impervious map with a broad area. In this study, segment-based impervious surface mapping algorithm is proposed using the RapidEye satellite imagery in order to map impervious area. At first, additional bands are generated by using TOA reflectance conversion RapidEye data. And then, shadow and water class are extracted using training data of converted reflectance image. Object-based impervious surface can be generated by spectral mixture analysis based on land cover map of Ministry of Environment with medium scale, in the case of other classes except shadow and water classes. The experiment shows that result by our method represents high classification accuracy compared to reference data, quantitatively.

• Journal of the Korean earth science society
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• v.45 no.2
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• pp.121-135
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• 2024

This study examined the influence of near-surface atmospheric warming in the Arctic-East Asia region during spring (March-May) from 1991 to 2020 on the synoptic-scale meteorology of dust storm-induced dust days in Seoul, Korea, in response to the Arctic Oscillation. Increased springtime warming in the Arctic-East Asia region correlated with a reduction of six days in the occurrence of dust storm-induced dust days in Seoul, Korea, along with a decline in the intensity of these days by -1.6 ㎍ m^-3yr^-1 in PM₁₀ mass concentration. The declining number of dust storm-induced dust days in Korea during the 2010s was the result of synoptic-scale meteorological analysis, which showed increased high-pressure activity as indicated by the negative potential vorticity unit. Moreover, a distinct pattern emerged in the distribution of dust storm-induced dust days in Korea based on the Arctic Oscillation Index (AOI), showing an increase in negative AOI and a decrease in positive AOI. Although the northward shift of the polar jet weakened the southerly low-pressure system activity over Mongolia and northern China, a reinforced high-pressure system formed over the Chinese continent during dust-storm-induced dust days with a negative AOI. This resulted in both a decrease in the frequency of dust-storm-induced dust days and reduction in wind speeds, facilitating their transport from source regions to Korea. Conversely, on days with positive AOIs, an extensive warm and stagnant high-pressure system dominated mainland China, accompanied by further cooling of the northern segment of the polar jet. A notable decline in wind speed in the lower troposphere across the Mongolia-northern China-Korea region diminished the occurrence of dust storm-induced dust days and also weakened their long-range transport.