• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 춘계학술발표회논문집
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• pp.131-137
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• 2004

GPS/Meteorology technique for PWV monitoring is currently actively being researched an advanced nation. We deal with the monitoring of GPS derived PWV during the passage of Typhoon MAEMI. Typhoon MAEMI which caused a series damage was passed over in Korea peninsula from September 12 to September 13, 2003. We obtained GPS-PWV at 17th GPS permanent stations. We retrieve GPS data hourly and use Gipsy-Oasis II software. The GPS-PWV time series results demonstrate that PWV is, in general, high before and during the occurrence of the typhoon, and low after the typhoon.

• 한국지리정보학회지
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• 제16권1호
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• pp.59-66
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• 2013

태풍이 해양을 이동할 때 해양환경은 물리 생물학적으로 한반도 주변해역에 영향을 미친다. 태풍이동의 결과로써 해양의 수직적 혼합과 용승작용은 해양 표층수 냉각을 유도하고 태풍의 경로에 따라 식물플랑크톤의 증가를 초래하며, 태풍 전과 후의 해양환경은 해양표층의 생물학적 변화에 중요한 역할을 했다. 비록 태풍 이동의 원인으로 해양 표층수의 냉각이 확대되지만, 엽록소, K490, SST와 같은 다른 물리-생물리적 반응은 서로 다른 경향을 나타낸다. 본 연구의 목적은 한반도 주변해역에 영향을 미치는 태풍 이동경로와 해색센서에 의해 관측된 해양환경변수를 비교하는데 있다. 부유물질, 흡광계수(K490), 엽록소와 같은 해양환경변수는 2002년부터 2005년 MODIS 자료가 적용되었다. 태풍이동 후 동해에서는 평균 엽록소 농도가 1-4배 증가하였고, 태풍 이동경로를 따라 태풍 이후 MODIS 엽록소의 평균 농도가 증가하였다. 그러나 제주도 해역은 동해역과 반대의 경향을 나타내었다.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2003년도 학술발표논문집
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• pp.75-78
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• 2003

This study is to present a method of land cover change detection by the typhoon RUSA (August 1 - September 4, 2002) using Landsat 7 ETM+ images. For the Namdae-cheon watershed in Gangreung, two images of Sept. 29, 2000 and Nov. 22, 2002 were prepared. To identify the damaged areas, firstly, the NDVI (Normalized Difference Vegetation Index) of each image was computed, secondly, the NDVI values were reclassified as two categories that the negative index values including zero are the one and the positive index values are the other, thirdly the reclassified image before typhoon is subtracted from the reclassified image after typhoon to get DNDVI (Differential NDVI). From the DNDVI image, the flooded and damaged areas could be extracted.

• 한국환경과학회지
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• 제20권9호
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• pp.1191-1203
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• 2011

In case of Typhoon Dianmu, the temperature, wind speed, wind direction and the rainfall per hour changed dramatically when the center of the typhoon passed through Gimhae. Such a change was commonly found in the regions where the center of the typhoon passed through but almost not in the regions far away from it. For example, in the case of Typhoon Malou where the center of the typhoon was far away from the observation site, such a phenomenon was not observed. The analysis of the vertical observation data showed that there was a little change in the wind speed and wind direction in the vertical direction in the case of Typhoon Dianmu of which center passed through Gimhae. There was a great change in the wind speed according to the height in the lower atmosphere just before the center of the typhoon approached the region. When the center of the typhoon was passing through the region, the vertical wind speed was decreased. However, the wind speed was rapidly increased again after the center of the typhoon had passed through the region. Unlike the Dianmu, the difference in the wind speed and wind direction between the upper layer and lower layer of the atmosphere was relatively great in the case of Malou.

• 대한간호학회지
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• 제33권6호
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• pp.829-838
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• 2003

Purpose: In South Korea, as growing the need of psychological support in disaster situation psychological assessment on stress after disaster is important to find out the factors affecting coping, and to plan intervention in the community. Method: The volunteers of Korea Redcross who live around K city, and the research team visited all homes at Jirye town, one of the high-impact area, 4 month after the typhoon. One of the family members who is over 18 years old, answered the self-report questionnaire composed of disaster experience, damage, exposure to traumatic event, and posttraumatic stress with IES-K (Impact of Event Scale-korea) He also, described his family members symptom related to re-experiencing, hyper-arousal, and avoidance. Six hundreds households were surveyed. Result: The prevalence of moderate to severe PTSD symptom was 36% of the subjects. The severity of PTSD was affected by gender, economic status and affected by damaged property, physical injury, worsening existing disease, getting infectious disease, amount of experienced traumatic event before disaster, warning, taking shelter, and subjects revealed differences in somatization as severity of PTSD. According to the description, community members had re-experiencing, hyper-arousal and avoidance. Conclusion: At a rural area, South Korea, community members have suffered from psychological distress after disaster. So psychological interventions are required as affecting factors and also to plan for warning and shelter in disaster situation is needed for preventing PTSD.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.718-719
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• 2003

It is very important to monitor change of a forest. We compare the different seasonal remote sensing data to detect forest damaged by typhoons and build a method to detect the area damaged by typhoons. Study site is located in western Oita prefecture. The multitemporal satellite dataset of this study were consisted of four Landsat TM scenes taken before and after the typhoons. As compared with non-damaged area, it was shown that the reflective characteristic of the damaged area becomes high by band 3, band 5, and band 7. These bands are effective in extracting the typhoon damaged area.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.918-921
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• 2006

The short-term variation of sea surface temperature before and after typhoons and increase of chlorophyll a concentration that accompany with the typhoons during summer in the East/Japan Sea were explored by satellite. Four typhoons (NAMTHEUN, MEGI, CHABA and SONGDA) and a typhoon (NABI) passed over the East/Japan Sea in 2004 and 2005, respectively. Decreasing of SST was observed in the every five typhoons, however the magnitude of SST decreasing were various from 1 to $5^{\circ}C$. Chlorophyll a increases were found after the typhoons (0.1-3 ${\mu}g$ $l^{-1})$ except NAMTHEUN, and the area was approximately included in SST decreasing area by the typhoons. It suggests that chlorophyll a increase was caused by nutrient input from subsurface layer by strong mixing. On the other hand, rarely chlorophyll a increase was observed in northern area of polar frontal zone, which is located in $38-41^{\circ}N$, than northern area, and chlorophyll a increase in coastal area was higher (more than 3 times) than offshore area. It might suggest that chlorophyll a increase in the East/Japan Sea is also related with the depth or nitracline depth that affects the amount of nutrients supply to the upper layer by typhoon mixing.

• 대한지리학회지
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• 제49권1호
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• pp.18-31
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• 2014

이 연구에서는 제주도 지역에서 태풍에 의해 야기되는 조풍(潮風) 발생 및 식생에 나타난 피해의 시 공간적 특징을 밝히고자 하였다. 이를 위해 2012년 8월 하순 제주도를 강타한 태풍 볼라벤(BOLAVEN)의 통과시 기상자료를 분석하고 이후 야외답사를 수행하여 제주도 식생에 나타난 조풍해 정도를 조사하였다. 그 결과, 조풍해는 주로 제주도 남부 및 동부 해안지역에서 발생한 것으로 나타났으며, 태풍이 동반한 강한 남동풍과 상대적으로 적은 강수량이 그 원인으로 분석되었다. 조풍에 의해 해안에서 약 8km 범위 내의 삼나무(Cryptomeria japonica)와 해안지역의 곰솔(Pinus thunbergii)을 포함한 대부분의 식생이 피해를 입었으나, 그 피해정도 및 회복력은 수종별로 차이가 있었다. 조풍에 의한 식생 피해를 줄이기 위해서는 강풍성 마른 태풍이 접근 시 조풍해 발생을 예측하고 방제대책을 마련하는 것이 필요하다.

• Ocean and Polar Research
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• 제27권1호
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• pp.25-34
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• 2005

Impacts of Typhoon Maemi on a soft-coral community located on subtidal cliff at Munseom, Jeju were investigated in this study using underwater photography. Typhoon Maemi hit Jeju Island in late September 2003 and its impact was strong enough to destruct most shallow water sessile benthos including soft corals. To estimate numbers and size of soft-coral colonies, a line transect was installed on the cliff at depth from 3 to 9 m and photographs were taken serially by every 1m. From each $1{\times}1m$ underwater photograph, species and size of soft-coral colony was determined. Number of soft-coral colony and its Percent coverage (PC) in each $1m^2$ quadrat was calculated. Soft corals Scleronephthya gracillium, Dendronephthya gigantea, D. spinulosa and D. castanea were identified from the photographs. Dendronephthya sp. was mainly distributed at 3-6m while S. gracillimum was mostly occurred at $6{sim}9m$. A survey conducted before the typhoon showed that number of the soft-coral colonies at $3{\sim}4m,\;4{\sim}5m,\;5{\sim}6m,\;6{\sim}7m,\;7{\sim}8m\;and\;8{\sim}9m$ was 17, 24, 20, 23, 18 and 30 $colonies/m^2$ or 21, 48, 36, 28, 24 and 43%, respectively. After the typhoon, number of soft-coral colonies in the transect increased, 31, 35, 21, 10, 21 and 50 $colonies/m^2$ while PC was remarkably decreased as 21, 23, 21, 5, 9 and 13%, respectively. Our data suggested that the impact was limited in larger colonies; larger soft coral colonies were selectively destroyed and removed while the small colonies underneath the larger colonies remained undestroyed.

• 대기
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• 제16권1호
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• pp.19-31
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• 2006

The purpose of this study is to develop the statistical model to predict sea level pressure of typhoon period in south coast of the Korean Peninsula. Seven typhoons, which struck south coast of the Korean Peninsula, are selected for this study, and the data for analysis include the central pressure and location of typhoon, and sea level pressure and location of 19 observing site. Models employed in this study are the first order regression, the second order regression and the neural network. The dependent variable of each model is a 3-hr interval sea level pressure at each station. The cause variables are the central pressure of typhoon, distance between typhoon center and observing site, and sea level pressure of 3 hrs before, whereas the indicative variable reveals whether it is before or after typhoon passing. The data are classified into two groups - one is the full data obtained during typhoon period and the other is the data that sea level pressure is less than 1000 hPa. The stepwise selection method is used in the regression model while the node number is selected in the neural network by the Schwarz's Bayesian Criterion. The performance of each model is compared in terms of the root-mean square error. It turns out that the neural network shows better performance than other models, and the case using the full data produces similar or better results than the case using the other data.